Jonathan Reichental

Cheat Sheet / Updated 04-12-2024

A wide range of tools is available that are designed to help big businesses and small take advantage of the data science revolution. Among the most essential of these tools are Microsoft Power BI, Tableau, SQL, and the R and Python programming languages.

Article / Updated 07-12-2023

You’ve decided that a smart city initiative is right for your community. You now have a bold and ambitious vision. It’s time to get started so that you can actually realize this vision. You must initiate a process of translation to move from your smart city vision to a set of actions. For this, you need a plan. Do not let the enthusiasm for progress and results curtail the essential and sometimes tedious upfront work of strategic planning for you smart city. This popular adage is a favorite of mine: Failing to plan is planning to fail. You always increase the chances of success in an effort if you have a plan. (Having a Plan B is a good idea, too.) Most people have some sort of plan in place when they embark on a major work project. But is it a viable and flexible plan? Is it a plan that can actually absorb the pummeling a long-term effort will experience and still succeed in its goals? There’s a big difference between having a plan and having a great plan. What you need in order to get started is a process to define the strategy of how your smart city vision will be realized. You need a systematic process of envisioning and executing the steps to a desired future. Urban planning and development are typically deliberate and detailed activities. A smart city initiative is fundamentally an urban plan and therefore requires much of the same rigor. You’ll make complex decisions that include trade-offs and compromises, and you’ll do all this with many other stakeholders. The art and science of strategic planning is a repetitive, inclusive, often exhaustive exercise, which is a characteristic of much of the work in the public sector. You really do produce better results when you include as many people (those who can add value) as possible in almost any process. People want to be involved, and they want to have a voice in decision-making. After all, decisions that are made that affect the nature of a city have the potential to impact a lot of people. Everyone is better served when input is derived from the broadest set of participants. A strategic plan is a living document. That is, it is never locked down. It must be open to revisiting and to making course corrections as circumstances dictate. The plan must also be an artifact that’s referenced often, and progress must be measured against it. The worst strategic plan is the one that’s developed and agreed on and then never consulted. It’s the one that sits on the shelf, gathering dust. It’s pointless, and even soul-destroying. A strategic plan must be shared widely. It becomes a communication tool that helps stakeholders know what’s happening and when events will take place. The plan must be posted for easy access and made available in both electronic and physical forms. Your smart city initiative should have a dedicated website, or at least a dedicated section of your city’s website. A large number of people — ranging from community members to city staff and from other cities to the vendor community and more — will be interested in what’s coming their way. It’s worth spending the time to create a well-developed strategic plan. From better outcomes to clear directions for all who are involved and impacted, the benefits are numerous. But let’s be sober about this point: Creating a well-developed strategic plan is difficult, and the plan can be contentious. Be ready for the work ahead. Sure, it’s hard, but it’s well worth it. Perhaps this deserves a new adage: Preparing a well-developed plan is planning to succeed. Developing a strategic plan for your smart city Though business books might use different terminology, critiquing several of them reveals a consistent set of logical steps to move from an idea or need to a result. Whether it’s creating an art piece, developing a project, or planning a strategy, the following four steps typically spell out what needs to happen (Let’s call them the four D’s): Define. Design. Develop. Deploy. Some form of measurement should be baked in, too, to hold everyone accountable. Look below to see how this process can be applied to the development of a smart city. Keep in mind that the work of urban planning and development is never done, so by extension, it’s a little misleading to think in terms of completing a smart city. It’s a topic of considerable debate. (Another, similar debate involves determining which city in the world is “the smartest.” It’s not a fair question — each city is smart to the degree that it reflects the needs, culture, and aspirations of its citizens.) Returning to the idea of the process of creating a smart city (assuming the assertion that, by definition, this process can never be completed), it should be clear by now that this may be an iterative process. Thought of another way, smart city efforts may have phases, and they may be redefined as time passes. This topic gets a lot of attention because it directly relates to how you might think of scoping the smart city strategy exercise. Specifically, what are you including in the scope of the process to define, design, develop, and deploy? The answer is that you and your teams must decide what to include. Having a vision that may take a decade or more to accomplish is reasonable, but, realistically speaking, it’s likely a series of shorter actionable and consecutive strategic plans rather than a single big plan. Therefore, you should focus on the activities that are doable, relative to the larger vision, with the understanding that you’re dealing with a shorter time horizon. Take another look at the image above. Strategic planning involves Steps 1–4. The first step is to create your smart city vision. The next step is to define your goals —the desired results of the vision broken into specific, measurable areas. Moving from vision to goals, which is an exercise that is fun and critical, requires what is called the envisioning process. Envisioning a smart city At its core, envisioning is an interactive process for engaging stakeholders in imagining a desired future and identifying the activities in support of realizing it. It can be thought of as a more rigorous brainstorming process. Envisioning takes many forms: It’s performed at the beginning of an initiative but can also be used at various other times during the course of an initiative if it’s deemed valuable. Done well, envisioning can bring with it many of the following advantages. It Gets everyone on the same page Identifies creative ideas Builds cohesiveness in a group Enables all voices to be heard Supports achieving consensus Reduces the risk of pursuing ideas that may not be practical To help guide you through the envisioning process that forms the basis of your strategic plan and goals, follow these steps : Define the scope of your smart city vision. Using the smart city vision that has been already determined, identify and debate (using the tools of your choice) the major city areas within the scope. Though it’s tempting to use only existing challenges to lead the process, turn those challenges into what you want the city to become. For example, instead of saying “Fix transportation congestion,” perhaps consider saying “Implement innovative and efficient transportation options that provide more options and shorter trips.” The details of how you go about achieving these in-scope items come next. Create a short list of goals.Step 1 will likely result in a large number of scope areas. Be sure to validate them carefully against the agreed-on smart city vision. A scope item not aligned with that vision might need to be tabled, or it might mean that the vision needs expanding. Next, group together common scoping areas and consider new language to cover the range of these areas in a single goal statement. For example, many ideas might be related to transportation, but they should roll up to a master goal. Later, you will create objectives for these goals that will define specifics. Here’s an example of a transportation goal: “Create a transportation environment that is friendly to the environment, is efficient, and reduces parking needs by 60 percent.” There’s no hard-and-fast rule on how many goals you should have, but you should be guided by what’s possible. If you have 50 goals for your small city, well, you’re probably kidding yourselves. Each goal generates many objectives, which in turn generate even more projects. Be realistic about what’s achievable at least from the perspectives of capacity and budgeting. Consider a time frame.By definition, executing on a vision takes a long time. You’re certainly looking at several years, but not so long that it becomes impractical. Agreeing on a general time frame around the defined goals in Step 2 creates an important boundary and helps to sharpen everyone’s focus. Though recognizing that a smart city strategy is never finished, you must articulate a time frame for this round of visionary goals. Identify your city's strengths.This step requires some careful and honest introspection. Articulate your city’s qualities that lend themselves to the work ahead. Recognizing these strengths helps you focus everyone’s efforts, understand potential risks, optimize for strengths, and assist in prioritizing objectives. Create a first draft of Steps 1–4.Combine Steps 1–4 into a cohesive narrative. This isn’t an essay. It should begin with the agreed-on vision. Additional support for the vision can be considered — notes on how the vision was derived, including some background and motivation, for example. This is followed by each of the goals, listed in sequence. Under each goal, provide additional supporting details and desired outcomes, and specify how they align with the vision. Include a statement on how city strengths support each goal, give approximate timelines, and provide a proposal on how the goal may be measured. Don’t make the strategic plan document a massive tome. If it is, you’ve done something wrong. Make it succinct enough that most stakeholders are comfortable reviewing it and can recall many of its highlights. Circulate the draft to your smart city stakeholders.The next few steps are what is called rinse-and-repeat. The draft strategic plan for the future of your smart city must be circulated among a broad and diverse community. Create a mechanism to make it easy to elicit feedback and track changes. Review, redraft, and recirculate.The first round of feedback will likely elicit a high volume of comments. In subsequent circulations, you should expect reduced volume. Finalize and socialize.With several iterations completed, it’s time to lock down the document. It’s clear at this point which topics have resonated with your stakeholders. Try to engage the right talent to create the final strategy document. Make this document easy to consume — one that everyone is proud to reference and share. Make the document version-controlled because you’ll create many versions. Be comfortable having the document undergo regular reviews and updates. If changes are requested, follow a similar rinse-and-repeat process. You’ve reached the end of a major milestone in the strategic planning process. Now share it widely and often. With so many channels available for both analog and digital sharing, use them all. For the core online presence — possibly, a standalone website, or separate section of your city’s main website — consider a way for people to provide comments and information on how to reach members of the team. Converting your smart city vision to action Now that you’ve completed a high-level strategy document and it’s been endorsed by all the right stakeholders, you’re ready to move on to how the strategy will be put into action. The document so far includes your city’s vision for what it wants to become, and it lists the major goals that manifest the vision. Each goal is a specific area that articulates a desired future result within some defined period. A goal typically doesn’t provide the level of detail necessary to follow a set of steps. What you need are supporting objectives for each goal. These objectives then tie directly to projects, which is how the work gets done. (The image below should help you visualize the relationship between a vision, goals, and objectives.) What is an objective? It’s a specific action that supports a result in a defined time frame. It’s short-term with a clear definition and is a necessary building block in a strategic plan. Let’s use the example of transportation to explain how you take a goal and create objectives. In the example smart city, Goal 1 is to implement innovative and efficient transportation options. The smart city steering committee or the operations team may designate a group of people who will work on determining the supporting objectives for this goal. In a smaller city, assigning a new group may be impractical, so perhaps the operations team is appropriate to do this work. At minimum, people with the proper expertise should be part of the team. In this area, you definitely want experts in the transportation and planning areas, with input from public safety team members also potentially quite valuable. The team who is assigned should be fully aware of the purpose of the goal, the way it supports the vision, the desired timeline, and the manner it is being proposed to be measured. This content lies in the approved strategy document as it stands. Conducting interviews with relevant stakeholders is a good approach as well — it might mean reaching out to people who haven’t yet been engaged in the process. Stakeholders are both internal and external to the organization. Once the team is comfortable with scope, it’s time to think about objectives. You can follow any number of models, including brainstorming and design thinking. For more on the latter, check out Design Thinking For Dummies, by Christian Müller-Roterberg. The team must always be conscious of available capacity and funding and the timeline. Deviating from this guidance may result in objectives that, when reviewed, are quickly discarded and considered a poor use of everyone’s time. To return to the transportation goal,” here's what the objectives associated with that goal might look like: Goal: Implement innovative and efficient transportation options. Supporting objective 1.1: Support migration to electric vehicles by providing electric charging stations at 60 percent of city-provided parking spaces by 2025. Supporting objective 1.2: Upgrade all traffic signals to enable dynamic signaling based on real-time data by 2024. Examples here are deliberately lightweight for the purposes of simplicity and clarity. Your actual goals and objectives may be more detailed. Let your teams determine what’s appropriate for your agency and for the purpose of increasing understanding. It’s a good idea to include clear details on any mentioned technologies and unfamiliar terms. You want all stakeholders to understand what is being proposed. After all the goals have their associated objectives identified, you enter into a cycle of rinse-and-repeat, when the document is sent out for review and comment and then updated and reviewed again. This process repeats until general agreement is reached. The steering committee then needs to sign off on the approved objectives. Finally, the completed strategic plan should be brought to your elected officials, or the equivalent, for sign-off. Want to ensure your smart city is on the right path? Avoid these ten problems.

Article / Updated 07-12-2023

Beginning the journey to create a smart city is a bold and courageous first step. The risks and costs are high, and positive outcomes aren’t guaranteed. Most cities that haven’t yet committed to a strategy may be able to detect an element of inevitability that the day will soon come. Evolving needs and community expectations will demand it. The promise of new technology in solving urban issues and delivering better results is simply too compelling — and in some cases too urgent — to ignore. But you do need to recognize pragmatic hesitancy. Those risks and costs are concerning. Reputations are at stake. The work is difficult and complex. However, the day will eventually come when a vision and a plan for a smart city (or whatever other term is used) are demanded and when work will need to begin. Cities won’t be able to sit this one out. Action will be required. When the decision is made to move forward with a smart city strategy, it’s time to evaluate the risks and come up with steps to lessen the danger. That means an ongoing risk management strategy must be part of the work as well. Consider establishing a risk register — a tool for documenting risks and the actions taken to address each risk. Fortunately, many case studies are available for review from cities of all sizes all over the world. Learn from them. Here, you discover ten smart city pitfalls to avoid. If you avoid these pitfalls, you will certainly reduce risk throughout your smart city program. But this is only one short list: Do your homework and identify issues that may be specific to particular initiatives — for example, around energy, transportation, health, or drone usage. It’s smart to be smart about smart city risks. Making your smart city project a tech program and putting IT in charge With the focus of smart city work revolving around the use of technology, it seems intuitive to consider it a technology program. Following that logic, it would seem to make sense for many cities to assign the work to their information technology (IT) team. Both assumptions seem reasonable but may be mistakes. Certainly, smart city technology is a core requirement; however, this program is about people. Keep in mind that technology adoption is an enabler, not the outcome. You must always return to fundamentals. Smart cities are about improving the quality of life for communities. Use this core belief to drive the work, and remind stakeholders frequently. The risk of making a smart city strategy a technology program and assigning it to the IT team is high, for the reasons described in this list: Placing the focus on technology can alienate many stakeholders. They may feel that they cannot contribute because they have insufficient knowledge or prerequisite skills. The fact is, smart city programs have greater success when all parts of an agency and the community have high levels of engagement. Your IT leader and team, despite their brilliance, may not be qualified to take ownership of this multidisciplinary program. It’s a leap to assume that knowledge of technology equates to competence in running projects that span across city domains. Sure, your IT leader may be a superstar who has the capability and knowledge to lead a smart city strategy. In that case, embrace this approach. In most cases though, it’s unlikely. Placing the emphasis on technology may result in a program that receives less priority and attention than it deserves. The smart city program has the potential to be seen as simply another set of technology projects. The reality is that smart city work needs leadership at the highest level of the organization and that the focus at all times must remain on benefits to people. Despite any caveats you might be given, your IT leader and team must be essential and valued program partners. There’s little doubt that their contributions will be critical to the success of the smart city program. Garnering insufficient support and engagement from stakeholders for your smart city On any given day, a government agency is managing numerous projects. Big cities may even have hundreds of projects running, which is what consumes a good deal of city staff capacity. For this reason, the processes for identifying projects, getting them budgeted, and then executing them is fairly routine. More often than not, a project is managed and delivered by a single department. Sometimes, more than one department is involved, but an all-departments program remains quite rare. You should consider the smart city program an all-department effort. As a result of continuing routine practices, departments may be inclined to move forward with smart city projects with insufficient engagement. Sure, they’ll embrace their normal network of involved participants, but they may not extend across other city departments and deep into the community. It’s not deliberate — it’s just that everyone defaults to their own routine. After a smart city program is approved — the emphasis must be on stakeholder engagement. Spend some time determining who should be considered a stakeholder. Be liberal in your inclusion of people you may not typically consider. The work to create a smarter and more sustainable city is a long-term effort. Engaging stakeholders and advocating for success early is a valuable approach. After stakeholders are identified, you must work with them to include them in discussions related to defining the vision, agreeing on goals and objectives, identifying projects and vendors, and more. Engagement at this level builds trust among participants. It may create a heavier administrative burden, and it can slow the process, but the dividend makes it worthwhile. Certainly, a lack of support and engagement always guarantees bigger and more frustrating challenges. To be inclusive, use a variety of platforms that include everything from traditional in-person meetings to online collaboration tools. Limiting efforts to your smart city boundaries Suppose that the mayor proposes that your city work on becoming a smart city. It sounds like you need to build a vision and a strategy for your community. That’s reasonable. But wait — might there be an opportunity to engage participants outside the city limits? All too often, the natural inclination is to focus solely on a single city. It makes sense on many levels. However, is it possible to be completely successful if the broader world isn’t considered? The term broader world may refer to adjoining cities or to the local region. It may also mean engaging with federal organizations. Cities don’t exist in a vacuum. They are entirely dependent on their interdependence with other communities and external organizations. Here are some examples: Public transportation: A public transportation system that serves a region can’t be considered only in the context of a single city or a few cities. If your smart city work impacts public transport, you need to engage with regional transport providers. Public safety: Your city might invest heavily in new technology to combat crime, but if you limit that work to your city’s borders and fail to engage surrounding communities, you might be restricting the effectiveness of your efforts. Environment: One of the most obvious suggestions for engaging participants beyond your own city is any effort related to the environment and climate change. Most people acknowledge that humans won’t solve air, water, and climate issues, for example, by doing work in a silo. These areas don’t respect borders. The best outcomes will be achieved when collaboration exists at the regional and national levels, where appropriate. Finally, smart city leaders can explore regional efforts if it means sharing cost. It’s highly possible that the work you’re doing would be of interest to cities nearby. Go ahead and have that conversation with them. A smart city effort executed by several cities will reduce costs and may even be more successful due to regional collaboration. Even if it’s more difficult, the effort may well be worth it. You won’t know unless you explore it. Paying insufficient attention to inclusiveness issues Most everyone enjoys using new technologies. But there’s always a risk that deploying a new smart city technology and process may have a positive impact on one part of the community while overlooking, or even limiting, others. That is unacceptable. Cities belong to everyone. Cities must serve everyone. Private organizations may have the right to choose their customers, but cities do not and should not. For example, even when a city digitizes a simple analog process, such as putting a form online, it must retain alternatives for those who lack the technological savvy or access to the necessary technology. It’s a unique city characteristic and responsibility. Because smart city efforts can range in their impact on a community, careful consideration must be given to inclusiveness. Urban innovation has the real potential to create and increase social inequity. Specifically, in the design of a new service, teams must assess whether everyone who may be impacted by the change continues to be served with equal access, respect, and attention. Ensuring analog options for online services may be relatively straightforward, but many smart city projects involve both the digital and physical worlds. For example, services that use audio and visual cues must be accessible by those who have limitations in those sensory areas. Inclusive smart cities require broad community engagement and collaboration — and a commitment to human-centered urban design. To date, the lack of a focus on inclusiveness in smart city programs has been an area of notable criticism. It’s time to make inclusiveness a priority and a mandatory part of the work. Improving the quality of life in cities must not be an experience for only a subset of a community — it’s a goal that must benefit everyone. Moving forward with a smart city without adequate governance For many people, the term governance may not be familiar, but the purpose is typically well understood. Simply defined, governance involves the structures put in place by organizations and teams to achieve measurable results toward achieving their goals. These goals can include the strategy of an entire organization, a project, or a program. The structures of governance can include these tasks: Identifying leadership and staffing positions Defining reporting relationships to be put in place Determining how decisions on funding are made Choosing how issues are escalated Selecting which processes are adopted To launch a smart city program without agreement on a rigorous governance structure (also called a framework) is a recipe for possible failure. The skills in putting together a governance framework may not be present in many cities. This is why you’re encouraged to seek assistance from an external party. Good governance can produce good results. It’s worth the time and expense needed to produce an agreeable approach. You’ll know whether your city has good governance in place if qualities such as clear accountability, process documentation and transparency, specific role definitions, reporting structures, goals, objectives, program and project alignment with strategy, and metrics are all defined and agreed on. Consider these and more as the pillars of governance success. Working with no clear vision of the smart city program Let’s be honest: Running a small handful of technology-related city projects does not a smart city make. That’s just a handful of technology projects. The work to create a smarter community will likely be a multiyear effort with clear, bold, and ambitious goals. A meaningful shift must take place in terms of how services are delivered and operations are conducted. Quality of life should be measurably improved and experienced. This kind of game-changing work requires a vision — preferably, one articulated by way of a vision statement that includes a short description of what the organization wants to become. The vision, which is a signpost of where the enterprise is headed, guides all stakeholders in their decision-making and their actions. A smart city vision should be aligned with the city’s broader strategy and approved by the community. In fact, determining a vision for your smart city work is an important way to engage constituents. Don’t stop at the vision, either: It’s the starting point that gets converted to goals, objectives, and then projects. Deep engagement with city staff and community members helps to ensure that the right priorities are identified and there’s agreement on the work to be done. Bring lots of data to these decision-making activities. A great vision is a great start to your smart city work. Without this vision, you have no signpost. Later, you may find that this lack is a guarantee of facing program challenges further down the road. Make the creation of a smart city vision one of the first things your team does. Downplaying the essential roles that security and privacy play in a smart city A trade-off will continue to exist between the benefits that technology and data bring to the world and the attendant risks that come with them. As people acquire and deploy more digitally based solutions in their homes, businesses, and cities — and even on themselves — everyone clearly recognizes the many advantages that each new innovation brings. Emerging technologies are rapidly changing the world in surprising ways. What isn’t clear is the extent of any risks that each one may present. Part of the challenge is that the nature of the risks continues to evolve. Cybersecurity is a particularly dynamic space: The bad guys are generally outpacing anyone’s ability to fully protect software and hardware security vulnerabilities. Leaps in cybersecurity are being made, but a long road lies ahead if we humans are ever to have the upper hand in completely protecting our systems. One of the core by-products of city government services is the collection, management, and storage of data. It’s the one asset that every government has in abundance. Just consider all the services that need system and data support. The amount of data collected in forms alone is humungous for most agencies. Now cities are deploying an array of different sensors that capture details such as video, air and water quality, traffic information, and much more. All these devices collect and produce data. Though protecting city data has always been important, the volume, velocity, and variety of it now has significantly elevated the risks to it. As remarkable as it may sound, the responsibility and degree to which protections are put in place in many cities around the world is at each city’s discretion. That said, many efforts are taking place, ranging from new industry standards to new regulations and laws that are being applied. For example, the European Union's General Data Protection Regulation (GDPR) is a law that’s being enforced across member nations to protect the personal data of EU citizens. In California, the California Consumer Privacy Act (CCPA) is a similar law, albeit less restrictive, that attempts to protect the personal information of Californians. Not making cybersecurity and privacy a priority in all city operations today is a mistake. The financial costs, loss of organizational credibility, damage to brand, severe disruption of services, potential downstream crimes, and pain to individuals it may cause make the stakes simply too high. Your smart city strategy will increase these cybersecurity and privacy risks. As one public sector cybersecurity professional once advised, “We shouldn’t be creating smart cities — we should be creating safe and secure smart cities.” Sharing smart city successes and failures too narrowly Government workers often take the brunt of stereotyping that characterizes them as lazy and unproductive. A few of those might exist, but isn’t that true in every industry? The truth is often quite different. Often, these people are some of the most passionate, selfless, and hard-working people you’ll ever meet. Some of the work can be thankless, but still, so many do the necessary, routine work of ensuring that their government services can function. What also strikes many involved is the volume of important work that gets done that nobody notices and is never publicized. Few cities have marketing departments, in the private sector sense. Sure, they have communications teams who do vital work — such work may even include creating campaigns to attract businesses and tourists — but the everyday achievements of most cities are lightly reported on municipal websites and, at best, in local newspapers. In other words, cities can do a much better job of telling their stories. Given the broad interest in smart cities, this work has received more attention than many of the programs that cities work on. The scale and transformational potential of the work is attractive for journalists and analysts, and so a decent amount of new content is being produced on this topic. So much of it, though, is being led by third parties, not by the city itself. Managing the narrative may be limited to infrequent press releases. Cities need to tell their smart city stories. They need to do this as not only a marketing tool but also a way to keep their communities apprised and engaged. They also need to do it to help other cities. Of course, they’d love to share only the good stories and best practices, but enormous value lies in sharing the failures as well. Of course, no city leader wants to expose the bad things that happen, so this strategy won’t be wholeheartedly embraced. However, the value in sharing those failures not only demonstrates transparency and honesty but can also be helpful in communicating the complexity and difficulty of the work for the benefit of other communities. Embrace and share your smart city strategy strengths and weaknesses. More communities will reap the rewards of this approach and, as a result, many more may prosper. Wouldn’t that be a good thing? Sticking stubbornly to the old ways of doing things Most people love predictability. They enjoy their routines. It’s a lovely experience to visit a favorite restaurant after a long absence and find that the dish you love is still on the menu and tastes exactly how you remember it. But predictability and routine in a work context — particularly, as humans traverse the fourth industrial revolution — may not be that desirable. This isn’t a reference to the comfort of a paycheck or the reliable trust of a colleague. Mostly, this refers to the need for organizations to change — often quickly — to respond to a world in transition. The biggest risk to organizations today is the lack of relevancy. If you’re doing the same thing while everything around you (including your customers) is changing, you’re not demonstrating your relevancy and you’re likely on a trajectory toward failure. Continuous modifications of products and services, and even operations, is becoming a characteristic of the times. The ability to evolve and reinvent at a moment’s notice appears to be emerging as a competitive advantage. In city government, change often happens slowly, and for plenty of good reasons, such as not having the budget to change or not wanting to upset a community by introducing a new process or having little appetite for even a modest amount of risk. Each of these is a legitimate concern and must be respected. But can the slow pace of city government innovation and a conservative mindset be sustained and acceptable when the world is rapidly changing? With city complexity and community expectations increasing, and with a growing number of intractable issues emerging, business-as-usual for a city appears to be under pressure. Because a smart city strategy is often a response to these challenges, this means that the capacity to embrace change must also expand. Sticking to the old ways of doing things while simultaneously pursuing a smart city program would appear to be incompatible. Leaders who are more flexible, ready to change, and prepared to take more risks may drive more success in their efforts than those who cling to the predictability of the ways things have always been done. Thinking too short-term when developing your smart city goals Depending on the political system of a city agency, projects may be tied to the term of leadership. In the United States, terms typically last four years, so many initiatives are targeted to kick off and be completed in that period. Though getting the right things done well is the purpose of leadership, it’s reasonable to also say that there may be additional motivations too. For example, if the initiative is a success in a single term, an official may take credit for the change and also increase their chance of being reelected or appointed to another term. Sometimes the reason for the timing is that the budget exists and the need is now greatest. There are a whole lot of reasons why, and when, work is done in a city. Many are specific to the particular city. It’s fair to say that many smart city projects can be completed in a reasonably short period (at least in a city context). For example, it’s possible to create and deploy apps that can be quite useful to a community well within a four-year time period. That said, the complexity and reach of an entire smart city program will likely stretch over much longer periods. A smart city strategy typically has bold and ambitious goals. It requires a lot of individual projects, many of which are interdependent and require new, complex software, hardware, and process requirements. You can easily fall into the short-term trap, where the team is looking just a few years into the future. Like everyone, they’re impatient to realize successful outcomes. A more pragmatic approach to the smart city work is to see it on the short-, medium-, and long-term horizons. As Steven Covey, educator and author of The 7 Habits of Highly Effective People, has famously said, “Begin with the end in mind.” A smart city strategy requires a long-term mindset, but with a focus on delivering value along the way. Too much short-term thinking may result in these errors: Incorrectly setting expectations for the organization and community Underspecifying the overall smart city architecture Poorly communicating the long-term budgeting requirements Sprinting at the start when everyone should be preparing for a marathon A smart city strategy is a long-term effort. Plan for it. Want to see some examples? Check out these smart cities.

Article / Updated 01-31-2023

Listen to the article:Download audio To be effective at their jobs, staff in an organization want to find the data they need quickly, and they want it to be high-quality data. This means the data needs to be accurate and current. Leaders want data to provide the basis for rich insights that enable timely and informed data-driven decision-making. The legal department requires data to be handled by everyone in a manner consistent with laws and regulations. Product designers want data to inform creative decisions that align with marketplace demands and customer trends. Security professionals are tasked with ensuring that the data is appropriately protected. Undoubtedly, a wide range of stakeholders want to harness the remarkable power of data. To achieve these and other increasingly common business demands, you need some form of data control and accountability in your enterprise. Quality results require the diligent management of your organization’s data. Data governance is all about managing data well. Well-managed data can drive growth Today, when data is managed well, it can drive innovation and growth and can be an enterprise’s most abundant and important lever for success. Well managed data can be transformational, and it can support the desirable qualities of a data-driven culture. This is when decisions at all levels of the organization are made using data in an informed and structured manner such that they deliver better outcomes internally and to customers. Research confirms that most business leaders today want their organizations to be data-driven, but, according to a survey by NewVantage Partners, only around 32 percent are achieving that goal. Successful data governance also means that data risks can be minimized, and data compliance and regulatory requirements can be met with ease. This can bring important comfort to business leaders who, in some jurisdictions, can now be personally liable for issues arising from poor data management. Every organization manages data at some level. All businesses generate, process, use, and store data as a result of their daily operations. But there’s a huge difference between businesses that casually manage data and those that consider data to be a valuable asset and treat it accordingly. This difference is characterized by the degree in which there are formalities in managing data. Broadly, the discipline in which an organization acts in recognition of the value of its information assets (a fancy term for data with specific value to an organization, such as a customer or product record) is called enterprise information management (EIM). Governing and managing data well is a central enabler of EIM, which also includes using technologies and processes to elevate data to be a shared enterprise asset. Data governance versus data management Within the EIM space there are many terms that sound like they might mean the same thing. There is often confusion about the difference between data governance and data management. Data governance is focused on roles and responsibilities, policies, definitions, metrics, and the lifecycle of data. Data management is the technical implementation of data governance. For example, databases, data warehouses and lakes, application programming interfaces (APIs), analytics software, encryption, data crunching, and architectural design and implementation are all data management features and functions. Data governance versus information governance Similarly, in EIM, you may want clarity on the difference between data governance and information governance. Data governance generally focuses on data, independent of its meaning. For example, you may want to govern the security of patient data and staff data from a policy and process perspective, despite their differences. The interest here is on the data, not as much on the business context. Information governance is entirely concerned with the meaning of the data and its relationship in terms of outcomes and value to the organization, customers, and other stakeholders. You might experience obvious overlap between the two terms. For sure, as a data governance practitioner, to some extent you’ll be operating in both the data and information governance worlds each day. This shouldn’t present an issue as long as the strategy for data governance is well understood. My view is that understanding the context of data, a concept known as data intelligence, and the desired business outcomes, complement data governance efforts in a valuable manner. The value of data governance If an organization considers data to be a priority and it puts in place processes and policies to leverage the data’s value and reduce data risks, that organization is demonstrating a strong commitment to data controls and accountabilities. In other words, that organization values data governance. An increasing number of businesses value data governance; in fact, according to Anmut, a data consultancy, 91 percent of business leaders say that data is a critical part of their organization’s success. Fundamentally, data governance is driven by a desire to increase the value of data and reduce the risks associated with it. It forces a leap from an ad hoc approach to data to one that is strategic in nature. Some of the main advantages achieved by good data governance include: Improved data quality Expanded data value Increased data compliance Improved data-driven decision-making Enhanced business performance Greater sharing and use of data across the enterprise and externally Increased data availability and accessibility Improved data search Reduced risks from data-related issues Reduced data management costs Established rules for handling data Any one of these alone is desirable, but a well-executed and maintained data governance program will deliver many of these and more. In the absence of formalized data governance, organizations will continue to struggle in achieving these advantages and may, in fact, suffer negative consequences. For example, poor quality data that is not current, inaccurate, and incomplete can lead to operating inefficiencies and poor decision-making. Data governance does not emerge by chance. It’s a choice and requires organizational commitment and investment.

Article / Updated 12-07-2022

In general, the definition of a data governance tool is one that assists in the creation and maintenance of policies, procedures, and processes that control how data is stored, used, and managed. No doubt, many aspects of data governance are complex, particularly in larger organizations. Fortunately, as expected from a competitive marketplace, where there is opportunity, you will find providers and their software solutions only too willing to help. As data has grown in its significance to every organization, particularly in just the last few years during the Cambrian explosion of data, many innovative data tools have been introduced. Some of the software has emerged from the largest technology players, such as Microsoft, Oracle, IBM, CA, Informatica, and SAP, but also mid-sized and even startups have entered this lucrative space. I’m not going to list solutions here, as there’s always a risk of implying some bias or leaving out an obvious player, plus, and this is probably the bigger reason, the marketplace is changing too fast and any list I provide will inevitably be dated quickly. The quantity and quality of innovative data tools recently introduced have been game-changers. The figure below is illustrative of many of the areas now addressed with software tools. With the increasing use of technologies, such as artificial intelligence, data management, governance, and analytics (and frankly, all aspects of data science) organizations have benefitted from increased automation, better decision-making, improved efficiencies and speed, higher data quality, greater compliance, and even the ability to contribute to increased revenue. To achieve these potential benefits, it’s certainly important for your organization to evaluate what tools may make sense. Selecting data governance tools Determining what tools you need, like so many things, depends on several factors. Considerations will often include: Business priorities and requirements The suite of data tools already available in the organization The complexity of data environment The complexity of IT infrastructure Current maturity level of data governance A narrow or broad focus of data governance objectives Skill sets of data governance team and data staff across the organization Available budget Data governance team appetite for automation and system administration Tool requirements may emerge out of an existing pain point, like so many solutions do. But deciding on a toolset may also be the product of a requirements-gathering process that considers the items in this list and others. Some of the common features now found in data governance tools include: Data discovery, collation, and cataloging: A mechanism to identify, collate, and support data set search. Data quality management: Tools that identify and correct flaws, cleanse, validate, and transform data. Master data management (MDM): This is covered earlier in the chapter in the “Master data management” section. Data analytics: An application to enable the discovery of insights in data. Reporting platform: A solution to generate all manner of business reports. Data visualization: An application that uses graphical elements as a way to see and understand trends, outliers, and patterns in data. Data glossary and dictionary: A repository that contains terms and definitions used to describe data and its usage context. Compliance tools: Solutions that automate and facilitate processes and procedures that support industry, legal, security and regulatory and compliance requirements. Policy management: A tool that helps in the creation policies, supports their review and approval, distributes to impacted staff, and can track that team members have received or viewed content. Data lineage: A solution that identifies, maps, and explains the source and destination of data, including its origin and stops along the way. Data lineage is also known as data provenance. Keep in mind that some tools are designed to do one or more of these tasks really well, while other solutions try to provide an entire suite of solutions. Needs, cost, and complexity are factors when determining whether to buy a single feature or full-suite solution. DataOps and DevOps A defining characteristic of the early years of the 21st century is the need to innovate at speed. In an unforgiving marketplace, organizations that are slow to improve their internal processes or cannot bring products and services to the market are at a disadvantage, which can result in business failure. In this context, greater emphasis has been placed on finding ways to accelerate innovation and produce more frequent deliverables. With technology playing such a central role in innovation, it was observed that the relationship between teams that created solutions — primarily based on software — and those responsible for deploying and supporting the code, were not aligned. These two groups, the developers and the IT operations teams, for example, reported to different leaders and had dissimilar performance goals. Around 2007, a movement started to better integrate development and operations that was aptly named DevOps. DevOps is a reimaging of how to build and deliver solutions quickly. It incorporates automation, collaboration, communication, feedback, and iterative development cycles. In a similar fashion, but on the premise that organizations were struggling with data volume and velocity, and the slow speed of deriving insights, it was observed that efficiencies could be gained in rethinking the lifecycle of data within the enterprise. Using the concepts and successes of DevOps, around 2014, a new approach to data analytics emerged called DataOps. Some called it DevOps for data science. The figure below shows the data management areas that are being automated — the shaded areas — with DataOps. Like DevOps, DataOps uses contemporary work approaches such as collaboration, tools, and automation to find efficiencies and deliver higher quality and quicker insights. You can think of DataOps as a way to kick data analytics into high gear. Central to DataOps is the emphasis on collaboration between participants in the data value chain. This includes data analysts, data engineers, IT team members, quality control, and data governance. In addition, like DevOps, DataOps proposes an agile approach to delivering data solutions. Instead of long periods of requirements analysis, design, and then development, work is broken into smaller chunks and priority is given to delivering value quickly and often. Cycle times are compressed, and business users get the data they need sooner. As an example of inefficiencies in the absence of DataOps, a marketing leader requests the development of a new monthly report. In traditional development lifecycle organization, it can take weeks and even months to elicit and validate the requirements for the report, design and develop it, receive feedback and make changes, and then deploy it. The long cycle times lead to disappointment and missed opportunities, and it deters data requestors from even making requests. DataOps changes the game on requests like these through a mix of agile methods, improved collaboration, and automation. Recent research revealed that many companies that embraced DataOps and agile practices were experiencing a 60 percent increase in revenues and profit growth. DataOps can be implemented through team structuring and new processes. But it can also be facilitated through new supporting tools that include artificial intelligence and automation. A dynamic marketplace has emerged that will provide you with many options and new capabilities to accelerate your data analytics cycle times. DataOps is a type of data governance in that it focuses on improved and faster methods to deliver more data value and quality while also considering risk. In addition, it requires the participation and support of the data governance team to help with policies, standards, quality control, and security considerations. DataOps tools can also give data governance teams new, actionable visibility to data use, flow, and challenges in the organization. Some say DataOps is the future of data governance. The evidence is certainly pointing in that direction.

Article / Updated 12-07-2022

You can’t buy a data governance program off-the-shelf. That’s actually good news. Organizations must implement a program relative to its level of interest, as well as its needs, budget, and capabilities. Even a modest effort can produce meaningful results. Glancing at all the areas in the figure below may seem overwhelming, but not all of these elements need to be addressed (certainly not at first), and there are different degrees in which each can be pursued. As you read and learn about them in this book, you can decide what makes most sense for your organization. Regardless of how and to what degree you implement the elements of a data governance program, you’ll need a basic set of guiding concepts and a structure in which to apply them. This is called the data governance framework. While there are many framework variations to choose from, including ISACA’s Control Objectives for Information and Related Technologies (COBIT) IT governance framework, they share some common components that address people, process, and technology. I’ve done the hard work of distilling down the most important qualities of a data governance framework and captured them in the figure below. These components are explored in detail in the book Data Governance For Dummies. It covers everything you need to know about how to implement a basic data governance framework. The data governance components in this figure are not in a specific order, with the exception of leadership and strategy, which is a prerequisite for the rest of the framework. Leadership and strategy Your data governance program must be aligned with the strategy of the organization. For example, how can data governance support the role that data plays in enabling growth in specific markets? Data plays a role in many aspects of organizational strategy, including risk management, innovation, and operational efficiencies, so you must ensure there’s a clear alignment between these aspects and the goals of data governance. The disconnect between business goals and data governance is the number one reason that data governance programs fail. When mapping organizational strategy to data governance, you need the support, agreement, and sponsorship of senior leadership. I’ll be blunt about this: Without full support from your organization’s leaders, your data governance efforts won’t succeed. Roles and responsibilities Your data governance program will only be possible with the right people doing the right things at the right time. Every data governance framework includes the identification and assignment of specific roles and responsibilities, which range from the information technology (IT) team to data stewards. While specific roles do exist, your organization must understand that data governance requires responsibilities from nearly everyone. Policies, processes, and standards At the heart of every data governance program are the policies, processes, and standards that guide responsibilities and support uniformity across the organization. Each of these must be designed, developed, and deployed. Depending on the size and complexity of the organization, this can take significant effort. Policies, processes, and standards must include accountability and enforcement components; otherwise it’s possible they will be dead on arrival. Metrics The data governance program must have a mechanism to measure whether it is delivering the expected results. Capturing metrics and delivering them to a variety of stakeholders is important for maintaining support, which includes funding. You’ll want to know if your efforts are delivering on the promise of the program. Based on the metrics, you and your team can make continuous improvements (or make radical changes) to ensure that the program is producing value. Tools Fortunately, a large marketplace now exists for tools in support of data governance and management. These include tools for master data management, data catalogs, search, security, integration, analytics, and compliance. In recent years, many data science-related tools have made leaps in terms of incorporating ease-of-use and automation. What used to be complex has been democratized and empowered more team members to better manage and derive value from data. Communications and collaboration With the introduction of data governance and the ongoing, sometimes evolving, requirements, high-quality communications are key. This takes many forms, including in-person meetings, emails, newsletters, and workshops. Change management, in particular, requires careful attention to ensure that impacted team members understand how the changes brought about by the data governance program affect them and their obligations. A large number of disparate stakeholders need to work together in order to effectively govern data. Collaboration is essential and can be the difference between success and failure. Good collaboration requires a positive culture that rewards teamwork. It also requires clear channels between teams, such as regular meetings. Online collaboration platforms are increasingly being used too.

Cheat Sheet / Updated 11-29-2022

This Cheat Sheet summarizes two important aspects of data governance: creating policy documents and the responsibilities of a data governance council.

Article / Updated 10-18-2022

There may actually be no such thing as a smart city. Wait — what? That’s certainly an odd comment coming from an article about smart cities. Okay, let’s explain. There’s no such thing as a completed smart city. It would be difficult to find an example where all the work has been finished and the designers and implementers have, after completing their tasks, washed their hands and said, “We’re done. Voilà! Here’s your smart city.” Nope. Doesn’t exist. After all, is a city ever completed? With a few rare exceptions, cities are in a constant state of change. Whether they’re being updated and improved or expanding upward, downward, and outward (or all of these); our cities are living, evolving entities. Cities are a work in progress. They are shaped by (among many factors) community needs, by societal trends, by crisis, and by better ideas. They shrink and expand, they decline and are reborn, and they are destroyed and rebuilt. They are never finished. And so it’s a logical return to the idea that there’s no such thing as a smart city. Instead, there are compelling and urgent needs, and a necessary response to demands, for cities that function with greater “smartness” to be smarter in all areas and in every way. A smart city isn’t a city that has merely achieved some level of satisfactory smartness. A smart city is one that identifies with the need to be smarter and then bakes that knowledge into its functioning, action-oriented DNA. It doesn’t continue to use obsolete 20th century solutions. A smart city implements 21st century solutions for 21st century problems. If there’s one aspect of smart cities that can be chastised for continuing to cause confusion and excessive debate, it’s the absence of agreement on the definition of the term smart city. Here you get a brief breakdown of what constitutes a smart city and what does not. What a smart city is As Sicinius, the bearded protector of the Roman people’s interests, states in Shakespeare’s play Coriolanus, “What is the city but the people?” Indeed, what is the city but the people? This is the right place to start when discussing the future of cities. After all, cities are defined by the human experience. They exist in support of people, are the invention of people, and deeply reflect a people's culture. In Bangkok and Tokyo, the city landscapes are replete with temples, like Budapest is with hot baths, Amsterdam is with coffee shops, and Vegas is with casinos. The feel, the look, the behavior, the heartbeat of the city — these are all a reflection of people. Cities communicate the history and life of those who live there. (Some like to say that architecture is the language of the city, which is a fitting way to look at things.) Across the planet, cities have emerged for different reasons, and their design has been shaped by various influences. There is no one-size-fits-all solution when it comes to cities. Though they share some common needs, such as energy, transportation, communications, and sanitation, they have as many differences as similarities. Sure, a city can be defined and categorized by such characteristics as its geography, governance, population, and infrastructure, but its purpose, needs, and culture cannot be so easily abstracted and normalized such that you can generalize about their nature. The uniqueness of each city must be viewed through this lens. Many cities suffer the same challenges. Finding a parking space, for example, is a universal pain. But the way problems are solved is often specific to each community. For every challenge that is similar, others are often unique. It’s this backdrop that is essential for an understanding of how to think about smart cities. To be able to confidently say that Barcelona and Dublin are smart cities (or are becoming smarter) means that there would need to be a globally agreed-on definition and an agreed-on set of extensive standards and measurements. These don’t exist, and they may never exist. Okay, to be fair, there are a small number of proposed and voluntary standards for smart cities. Two strong examples are: International Organization for Standardization (ISO), sustainable cities and communities; indicators for smart cities British Standards Institute, smart city standards The term smart city is much less important than the purpose of the work and the outcomes. In fact, to clear up confusion, many other terms are used that are all simply synonyms. They include connected city, hyperconnected city, intelligent city, digital city, smart community, and others. Smart city (or smart cities) is the term that has stuck. A smart city is defined by its people, not by some outside arbiter. If Helsinki believes that it’s creating a better quality of life for its people in its innovative use of technology, it has the right to call itself a smart city. John Harlow, a smart city research specialist at the Emerson College Engagement Lab, states that “smartness in cities comes from people understanding what's important to them and what problems they are experiencing.” The most basic definition of a smart city is one that responds to its citizens' needs in new and improved ways. You’ll learn more regarding this definition shortly, but first, some additional contextual basics. The future of humanity is firmly rooted in cities. For better or worse, as rural communities rapidly decline, immigration to cities is booming. By the end of the 21st century, all things being equal, most humans will live in urban settings. This remarkable shift will define the future more than just about anything else humans do (other than perhaps populating other planets). Despite our many misgivings, on balance, cities are largely a success story. More than anything else, they have lifted billions of people out of poverty, providing jobs, shelter, accessible healthcare, and other support systems and regulations to assist in life’s needs. Edward Glaeser, the American economist and author of Triumph of the City, makes a compelling case that cities are humanity’s greatest invention. But it’s been a tough, ugly journey. The world’s early cities weren’t pleasant places for most people, and suffering was common. Fortunately, cities are now in much better shape, and an urban migrant should find options and opportunities to at least have the choice of a better life. However, though conditions in general are better than they’ve ever been, the challenges presented by cities today are more complex in many ways and are vastly more difficult and expensive to solve. Here’s a list of just a few of the smart city challenges awaiting solutions: Overburdened and inefficient social support systems Transportation congestion and poor public-transport options Inequality Poverty Crime Homelessness Environmental damage Poor air quality Aging and broken infrastructure Lack of jobs Weak civic engagement Food insecurity Inclusiveness This list is only a small reflection of the massive number of unique challenges that cities on every continent have to address. But it should be suggestive to you of the type of work that lies ahead. An obvious question right now is this: Why haven’t humans solved these types of problems? Some of the answer lies in leadership priorities and insufficient budgets as well as in the scale and complexity of the problems involved. Clearly, if these problems were cheaply and easily solved, they’d have been addressed by now. They are neither. However, the history of innovation is a reminder that humans have the capacity to solve big, intractable issues. Improved sanitation changed the trajectory of healthcare, for example, and fertilizer made food abundant. Might innovation also help with the current challenges of the world’s cities? Many would argue yes, and technology powered innovation might offer some of the best opportunities. This kind of thinking may draw you closer to a definition of what a smart city is. The Smart Cities Council, a network of companies advised by universities, laboratories, and standards bodies, maintains that smart cities embody three core values: livability, workability, and sustainability. Specifically, the council states that using technology to achieve improvements in these three areas is the definition of what a smart city needs to be. So, considering everything you’ve learned so far, including researching the literature on the topic, what might a definition look like? Here’s a proposal: A smart city is an approach to urbanization that uses innovative technologies to enhance community services and economic opportunities, improves city infrastructure, reduces costs and resource consumption, and increases civic engagement. Fair? Many smart city definitions include references to specific technologies — often this is a mistake. The definition should be about outcomes, and it should outlive technologies that come and go. There will always be better tools in the future. Limiting a definition to tools that exist now will make any definition quickly outdated. Finally, don’t lose sight of these two important qualities that are essential for smart cities: Technology use: There are many ways to address city issues, but when technologies are used as the primary tools, this helps to make the city smarter. A smart city is a system of systems that optimizes for humans. People first: Don’t become too enamored by the use of technology. When deployed correctly, technology is largely invisible, or at least non-intrusive. What matters are the outcomes for people. A smart city is ultimately a human-centric endeavor. After all, what is the city but the people? What a smart city is not Establishing the definition of a smart city is vital because it helps you comprehend the scope of the topic. But recognizing what a smart city is not also has value. Here are five things that a smart city is not: An upgrade from a dumb city: There are many smart cities events each year, and inevitably a speaker or panelist makes a joke about cities being dumb before they were smart. The joke usually draws a chuckle. Fair enough — the notion of “smart” isn’t precise enough for what it is, but it’s the title that has stuck. All cities are complex, amazing feats of human creativity. They aren’t dumb and have never been — quite the opposite. Becoming a smart city is more about becoming smarter in the use of technology to make what the city does better and to provide solutions to problems that traditionally have been difficult to solve. One last, related point on this topic. One point of view is that a smart city can exist only with smart people. This perspective is far from fair or inclusive. Communities are made up of all types of people, and everyone, if they choose, has something to contribute. When building smart cities, ensure that all your efforts and experiences embrace the majesty of all people. You should, in fact, add this as a goal in your strategy. A surveillance city: Implementing a smart city should not mean the end of privacy for its residents, businesses, and visitors. It’s true that smart cities deploy sensors in support of their efforts — possibly for monitoring air and water quality, improved traffic management, noise detection, energy management, and much more. It’s important to acknowledge privacy concerns where they arise, and city leaders need to listen carefully and respond with assurances. However, you should recognize that these efforts are made to improve services, not to impinge on privacy or create a surveillance city where everyone is being monitored. In developing and executing on a smart city strategy, stakeholders must ensure that privacy is upheld, data is anonymized, and the community is engaged in the process to provide transparency and build confidence. Deploying smart city technology that includes sensors should be specifically and carefully regulated by rules — even legislation — in order to protect the community. Make that a priority. A strategy about gadgets and apps: Yes, technology is definitely at the center of developing a smart city, but if you look at many of the vendors in this emerging space, you can easily believe that the subject is really all about cool new toys and apps. Sure, plenty of those are available. However, transforming a city, solving complex challenges, and creating a higher quality of life for the greatest number of people are goals that require comprehensive changes in processes, rules, technologies, and the talent and skills to plan and implement it. Don’t be distracted by novel, piecemeal solutions. Sure, consider those factors in the mix, but recognize that creating a smart city is an undertaking that requires a significant focus on technology strategy, extensive solutions architecture, and systems integration. Remind yourself (and others) often that smart cities are about people, not technology. A temporary technology trend: You might believe that the smart city movement is a recent development, perhaps just two or three years old. In reality, applying technology to make cities operate better has been under way for several decades. It isn’t possible to determine the first-ever use of the term smart city, but it certainly has references at least to the early 1990s. Even with a reasonably long history already, the real action of smart cities is happening now, and the most significant results will be seen in the years ahead. More than some sort of temporary trend, for cities to function well and bring a high quality of life to as many people as necessary, the smart city movement will last for multiple decades. Though the smart city concept may change over time, the goal doesn’t really have an expiration date. For many skeptical city leaders, it’s time to shrug off the belief that it’s a passing fad and get on board to embrace the benefits of urban innovation. A concept that matters only to big cities: If you review the literature on smart cities, it certainly would appear that only big cities can be smart cities. The same names pop up all the time: London, Paris, Moscow, Melbourne, Dublin, Vienna, Barcelona, San Francisco, and others. Sure, these incredible cities have impressive smart city initiatives, but any city can pursue the goal of becoming smarter. After all, most cities in the world today are small. The big ones are the outliers. Interested in learning more? Check out our Smart Cities Cheat Sheet.

Article / Updated 07-28-2022

So you, your colleagues, and members of the community have decided that increasing the quality of life and solving complex challenges by using technology — coupled with data, new processes, and a progressive disposition toward innovation — is the right path for your city. You want to take a smart city approach going forward. Well done! No, seriously. The decision to act on something, to take a particular path relative to the action itself, can be the hardest part. It’s always possible to become entrenched in debate, to fail to find common ground, or to reach an impasse. But once some form of agreement is reached, even if just marginally directional, you should celebrate. Anyone who has worked on a project of some significance knows the difference between the big decisions and the many small decisions that happen. Without those big decisions, the project team might struggle. But it’s a great relief when direction is given. The project team can then move ahead with their work. One of the most important big decisions that has to be made at the beginning of a smart city effort is the establishment of a vision or vision statement. This vision is a top-level guide for almost all decisions to come. Singularity University has a term for efforts with a bold vision that motivates meaningful change. It’s called massive transformative purpose (MTP). An MTP is aspirational and focused on creating a different future. Realizing an MTP requires a mindset and work environment that leans into complex problems and strives to think big. MTP needs talented and dedicated teams working smartly with a huge amount of motivation. They have successes and sometimes failures. Creating a smart city may not be the equivalent of finding cures for all types of cancer, but the outcomes of smart city efforts are significant and can impact a lot of people. Consider your vision exercise as your MTP. The smart city movement remains largely in its infancy. The vast majority of cities in the world have yet to embark on this journey (assuming that it’s the right direction for many of them). They are starting from zero. As with any initiative, it’s easy to jump directly into the tactics after receiving direction to pursue smart city goals. But that would be a mistake. The first step on any smart city journey needs to be the establishment of an agreed-on vision. That vision guides strategy, and strategy directs the work. Identifying the role of leadership for your smart city Leadership and management are terms that are often used interchangeably. That’s a mistake. Although there are some underlying similarities, they are different. Each requires and utilizes a specific approach and mindset. Management is doing things right. Leadership is doing the right things. It’s an essential distinction attributed to the management guru Peter Drucker. It’s one of the reasons that management can be learned, but leadership has qualities that some fortunate people possess from birth and can’t be easily acquired by training — such as charisma. Sure, many aspects of leadership can be learned, but it’s obvious that remarkable leaders don’t necessarily acquire their skills from books. It’s a little frustrating for those trying to be great leaders when they realize that they can learn and practice most skills but will always have a deficit relative to those unique leadership qualities that require something special. That said, the body of knowledge today on leadership is enough to help most leaders acquire the essential skills. Any given leadership team will have some with learned skills and some with natural abilities. That’s the case on city leadership teams, too. Smart city work suffers without great leadership. After all, research from across all industries suggests that projects generally succeed or fail depending on the availability of consistent high -quality leadership support. Who are these city leadership teams, and what might their responsibilities be relative to smart city work? To answer these questions, city leadership has been divided into these four basic parts: Elected leaders: Assuming some form of democratic process, these leaders, which can include the popular role of mayor, are chosen by the city’s constituents via voting and serve for a predetermined period. This is by far the most common process. In some jurisdictions around the world, city leaders are appointed by other bodies. In either case, these leaders typically have the primary function of setting policy, approving budgets, and passing legislation. They may originate an issue to debate, or an issue may be brought to them by any number of stakeholders, from community members to city staff. For example, if city staff proposes the smart city effort, elected officials are responsible for suggesting modifications, requesting more information, and approving or declining the request. Elected leaders absolutely must sign off on the smart city effort — particularly the vision, goals, and, ultimately, budget. A healthy public debate by elected leaders on the merits of the smart city work is valuable, as is eliciting public comment. Appointed leaders: Running a city on a day-to-day basis requires a set of hired leaders. The city inevitably has some form of overall leader — the public agency equivalent of a chief executive officer (CEO), such as a city manager or city administrator. This leader has assistants, deputies, and an executive team that manages the various areas of the city. These areas may include transportation, public works, planning, energy, libraries, healthcare, technology, and many more. Big cities have a large number of managed areas. The city leader and the team have the primary responsibility to implement and maintain policies. They make daily decisions and ensure that the city is operational and responsive to community needs. These leaders also propose initiatives to elected officials. A smart city effort may originate this way. It’s also possible, for example, that a strong mayor will ask for staff to develop a smart city plan and propose it to the elected leaders for approval. Appointed leaders are accountable to elected leaders and, by extension, to the community. Leadership support and oversight: In this category, a small leadership team is tasked with originating a draft policy, recommendations, or other decision-making instruments on behalf of either the elected or appointed leaders. These teams, which have a guiding function, aren’t decision-making bodies. However, they are essential contributors toward city leadership. These teams can be permanent or temporary, depending on their function. For example, the elected leaders may opt to create a committee to oversee and make recommendations and provide reporting oversight on the efforts of a smart city initiative. The team may exist only as long as the smart city initiative continues. Alternatively, a city may have a permanent transportation committee whose role is to make recommendations on matters related to transportation. Because this area is often included in smart city work, it may be the body that’s approached for leadership input. These teams are typically made up of suitably qualified members of the community. Regulatory leadership: This category is a broad one, in order to capture a range of other leaders who may have input in a city’s decision-making process. The most obvious groups include those who make regulations at a regional or national level. For example, a national set of rules on how drones can be deployed in cities may be made by a leadership group outside of a particular city, but that city would be required to adhere to the rules. This can make sense so that all cities in a region or country follow the same set of rules. People often debate how much power a city should have over its operations relative to the power of those at the regional or national level. Cities clearly want as much autonomy as possible, but the benefits of standards at a national and even global level have important merit as well. An example of an area where a city can benefit from national decision-making in the smart city domain is telecommunications. A national commitment to supporting infrastructure standards, and also financial assistance, benefits everyone. An example of global leadership is managing the climate crisis. Even though cities and nations have to sign on, the leadership and guidance may come from a global entity. Creating a vision for your smart city Your city has decided to embark on a smart city journey. Great! Now it’s time to create a vision or vision statement. What is a vision, and how is it created? Here, you’ll see vision and vision statement used interchangeably. There’s little difference between them, other than the number of words. A vision generally takes a few paragraphs to describe. A vision statement is typically only a few words long. The intent is identical. A vision is a statement of what you desire the future to be. It’s not tactics or operations. It’s not projects or deliverables. It’s simply a statement that guides the development of a strategic plan — called the envisioning process — and the decisions made throughout the journey. To help you better understand the role of a vision in the strategic plan, let’s take a quick look at strategic planning: Strategic planning is the systematic process of envisioning a desired future and translating this vision into broadly defined goals or objectives and a sequence of steps to achieve them. Put another way, the strategic plan is the translation of a strategic vision into outcomes. A vision written correctly and agreed on by relevant stakeholders holds the initiative accountable and provides essential guidance in times of uncertainty. Though it’s easy to overlook or omit this step, its value can’t be overstated. Do it. You’ll be happy you did. A vision isn’t the same as a mission. An organization's mission is what it does and how it does it, and it includes its shorter-term objectives. Your vision is none of those things. It’s long-term and future-oriented, and it describes a big-picture future state. It has clarity and passion. Here are ten tips for creating an outstanding vision statement: Think long-term. Brainstorm what a big future outcome would look like. Choose the one that gains consensus. Use simple words. Don’t use jargon. Make the statement inspiring. Ensure that the entire vision statement is easy to understand. Eliminate ambiguity. Anyone should be able to have a common understanding of what's actually involved. Consider making the statement time-bound. For example, use language such as “By 2030 . . .” Allude to organizational values and culture. Make the statement sufficiently challenging that it conveys a sense of ambition and boldness Involve many stakeholders. Here are some brief vision statement examples: Ben & Jerry's: "Making the best ice cream in the nicest possible way." Habitat for Humanity: "A world where everyone has a decent place to live." Caterpillar: "Our vision is a world in which all people's basic needs — such as shelter, clean water, sanitation, food and reliable power — are fulfilled in an environmentally sustainable way, and a company that improves the quality of the environment and the communities where we live and work." Hilton Hotels & Resorts: "To fill the earth with the light and warmth of hospitality." Samsung: "Inspire the world, create the future." Smart Dubai: “To be the happiest city on earth.” Though vision statements are typically short, no rule prohibits a more elaborate vision. As an example, here are the goals of the San Jose, California, smart city vision: Safe city: Leverage technology to make San José the safest big city in America. Inclusive city: Ensure that all residents, businesses, and organizations can participate in and benefit from the prosperity and culture of innovation in Silicon Valley. User-friendly city: Create digital platforms to improve transparency, empower residents to actively engage in the governance of their city, and make the city more responsive to the complex and growing demands of the community. Sustainable city: Use technology to address energy, water, and climate challenges to enable sustainable growth. Demonstration city: Reimagine the city as a laboratory and platform for the most impactful, transformative technologies that will shape how people live and work in the future. Not convinced a smart city is needed? Check out the case for smart cities.

Article / Updated 09-18-2020

Technology is the heart of a smart city. But, where there’s technology, there’s data. And knowing how to manage that data in a smart-city context is absolutely essential. Cities with technology create a lot of data. With more systems and devices coming online every day, the volume of data produced, collected, and stored is growing rapidly. It’s not just information such as your Facebook posts, Instagram photos, Google searches, and online forms you fill out — it’s also all the data produced by the myriad of processes taking place behind the scenes. For example, just one self-driving car generates over 4,000 gigabytes of data for each hour of driving. Now multiply that by the millions of autonomous vehicles that will come online in the next few years and it’s clear that just this one type of urban activity will create a colossal amount of data. This colossal amount of data is called data exhaust. Though that’s an appropriate term for vehicles, it applies to all the data that spins off electronic transactions. Between this data exhaust and the growing number of interactions that people have with all their devices, data growth is headed off the charts. In fact, right now it’s over 2.5 quintillion bytes of data every day. The technical phrase for that scale is, “Dude, that’s a lot!” Here’s another mind-blowing fact. Considering all the data that’s been produced since people started using computers many decades ago, remarkably, 90 percent of all data ever created has happened in just the past two years. Technologists have come up with an appropriate term for this scale of data: big data. That isn’t exactly an inspired choice, but at least it's accurate. Every type of organization is now producing, collecting, and storing big data. The clever ones are using it to run their businesses better, to more deeply understand their customers, and to build new products and services. When organizations use data in a way that improves operations, increases their bottom lines, and helps them to outperform their competitors, they’re called data-savvy. This term indicates that they have recognized the value of data, developed the relevant skills to manage that data, and implemented a strategy to use data as a core instrument of organizational success. Kudos to them. The popular role of data today has created a marketplace with a broad range of software tools that help with analysis and decision-making. It has also created a high demand for data-related skills and has even helped establish a new branch of study and expertise, called data science. The private sector has recognized the value of data and data-savviness; rejecting the value of data is hardly conceivable in a for-profit organization. Other sectors of the economy have been slower to fully embrace their data love. Government has been a laggard, but those days are coming to an end. Today, government agencies — and cities, in particular — are jumping head-first into the realm of data science. In a field where everything is scarce, governments have an abundance of data. Governments create, collect, and store a wide variety of data sets that include ingredients such as crime reports, permits, library lending information, demographics, pavement conditions, geospatial features, tax information, project status, and so much more. With the addition of digital sensors across a city landscape, the amount and variety of data is set to explode in the years ahead. Using this government data to improve operations, make better decisions, build trust and transparency, and enable innovation solutions has the power to build better and smarter cities. The smart use of data is a fundamental aspect of a smart city. Enabling data-driven decision-making in a smart city When you learn to fly a single-engine plane, part of the training process requires you to rely on the instruments regardless of what your brain might tell you to do. You wear a special cap that prevents you from looking outside. The instructor puts the plane into an usual configuration — let’s say a climb with low power —in order to create the conditions for an emergency situation. The instructor then tells you to use only the instruments to recover the flight orientation to a safe flying configuration. What happens is that your brain receives signals from the body, such as information about balance, that tell you to take actions that are wrong. But if you rely on what the instruments are saying, you make the correct maneuvers. The first few times you do this exercise, you have to fight your brain. In other words, you have to trust what the instruments are telling you versus what your brain wants you to believe. This example is analogous to how you must treat data. Good data tells the truth. Even though you might often want to believe something else based on how you believe something should be or on instinct relative to experience, you need to become comfortable with using data to make organizational decisions. Data will provide important insight, but it won’t necessarily tell you what action to take. That part still largely remains a human function. You will need to consider context, politics, and economics, amongst many other factors. There’s room for tacit knowledge, intuition, and experience, but they should be used sparingly and likely only in combination with what story the data tells. In fact, you must become hungry for exceptionally good data. The more you have and the richer it is, the higher the likelihood of a more informed data-driven decision. Data leads to information that then becomes knowledge. This knowledge provides essential insights. It’s not uncommon now for leaders to feel constrained by not being presented with sufficient information to make an informed decision. A smart city cannot exist without the smart use of data. Managing data in a smart city It’s hard to think of an organization today that doesn’t use data in some capacity.: But, the existence of data within an organization doesn’t equate to any evidence that it’s being properly managed. Making a city smarter by using data as the rich, valuable asset it is requires the deliberate use of specialized tools, talent, and processes. Data has a lifecycle, from creation to retirement, and to glean its optimum value, this lifecycle must be managed — a process known as data management. Data management typically includes these activities: Having the ability to collect, create, update, and remove data across disparate systems Possessing the capability to retain data in various formats across different types of storage systems Ensuring the high availability of data to authorized users Maintaining disaster recovery options consistent with organizational needs Supporting data's utilization across different types of systems and solutions Managing data privacy and security Being able to archive and destroy data according to policy and compliance requirements These minimum data activities must be addressed in your data strategy. You can easily test whether data is being well managed in a smart city. Consider the following basic questions: Does every data set have an owner? Can authorized people access the right data when they need it? If a disaster — such as a cyberattack, a fire that destroys systems, or an accidental loss or deletion of files — occurs, is service restored quickly and without a headache? Can data move securely between people and systems in order to best leverage its value? Is talent readily available to produce reports, identify insights, and perform research with data? If the answer to these questions is generally yes, you’re in a better position than most. On the other hand, if any of these questions can’t be answered with high confidence, there’s a good chance you don’t have a data management strategy, or the existing strategy needs to be reworked. Many larger cities have already embraced data management, but many still need to elevate this competency to the mature level it deserves. Smaller cities, while recognizing its value, struggle with this topic because of challenges with insufficient budgets to afford data scientists and specialized tools. Some good advice is for all city agencies to create a data strategy that rightsizes it against needs and the available budget. For example, for a large city, hire a chief data officer (CDO), and for the smaller ones, find staff that are interested in the topic who can carry out data roles as part of their other responsibilities. Developing a data strategy for a smart city Cities must have a data strategy if they want to have operational excellence, increased quality of life, and better performance results. The purpose of a smart city strategy is to have a plan designed to achieve some desired outcomes. Recognizing that data is your friend and that it can provide enormous value in every aspect of building and operating a smart city means that you have to create a deliberate set of actions to achieve results. A data strategy is an agreed-on plan that all appropriate stakeholders sign off on. A mistake that many organizations make after developing a strategy is to blindly follow it, even as circumstances change. The right way to deal with a strategy is to regularly confirm with stakeholders that the desired outcomes are still relevant and, if appropriate, modify the actions periodically. After all, nothing stays the same. Organizational agility is a valued 21st century characteristic. The worst type of strategy is one that’s created and never acted on. Creating a strategic plan isn’t the goal — achieving your outcomes is. Many excellent strategic plans are sitting on the shelves of executives, simply gathering dust. A data strategy must include, at minimum: A description of the roles and responsibilities that various leaders and staff play in the management of data The capabilities desired from the supporting systems Any policy, legal, or regulatory requirements An articulation of how data value will be derived Creating a strategy for a smart city usually follows a sequence similar to this one: Agree on the vision for the smart city. Document and agree on the desired results (the vision) of the plan. It’s defining what you want the future to look like. Often, this is the hardest step. You might be surprised to discover the degree to which stakeholders aren’t on the same page when this exercise first begins. However, after all the arm wrestling and debating end, it’s gratifying when everyone does finally agree on the vision. Perform a gap analysis. A what? A gap analysis is the result of identifying the difference between where the organization’s current performance is and where you want it to be. For example, you might look at business metrics and determine where you are versus where you want to be. Only by completing a gap analysis can you take the next step and identify and define your objectives. Identify the objectives for the smart city. To reach your desired outcomes, often called goals, means that you need to have actions to get there. These are the plan’s objectives. They should be SMART: specific, measurable, attainable, realistic, and time-bound. Define how the plan and the outcomes will be measured. Okay, here’s another truism: What gets measured gets managed. Without metrics, how do you know whether you’re winning? Define those targets. Don’t overlook this essential part of the strategy. Get the right people to sign off on the smart city strategy. This step is important. Without the right people putting their signatures on the plan, you’ll experience issues later on. It’s much harder for a leader to argue that they didn’t support or agree with a plan if there’s evidence that they have endorsed it. Making the final sign-off less difficult can be achieved by engaging those leaders throughout the strategy creation process. Execute the strategy and evolve as necessary. Yup, do the work. During this essential phase you’ll be obtaining funding, identifying project resources, running projects, and training or recruiting the right talent to manage the outcome. Though this set of steps is applicable to creating a data strategy, it can be applied to any strategy. Use it every time you identify a goal and need to come up with a plan. Want to ensure your smart city is successful? Avoid these ten mistakes.