That insight from Jeff Bezos is important for founders to consider when building products and picking markets. It seems particularly relevant in the urban / govtech space right now. All we hear about is what’s going to change; no one will drive, everything will be monitored, the coast will be swallowed by rising tides. Those, and other predictions, may end up being true, but is there anything that won’t change over the next 10 years? What do we know, with certainty, will be true in cities a decade from now?

I submit the following list of things I believe will absolutely be true in a decade when it comes to cities. There is intentional vagueness in these statements (i.e. #1), and the most vague will likely be areas that present the best business opportunities.

1. People will need to get from Point A to Point B. Cities will be the primary facilitators of this movement.
2. Cities will need to understand and monitor how people get from point A to point B in order to provide the necessary infrastructure.
3. Cities will continue to borrow against their future in order to pay for this needed infrastructure.
4. Cities will be using outdated technology and people will complain about it. The outdated, legacy systems will just happen to be what is currently considered innovative.
5. People will need places to live, work, and play.
6. People will continue to have children and those children will need to be educated.
7. People will still buy things and at least some of that will happen in physical stores.
8. New forms of mobility will continue to be introduced and most will die after brief hype cycles.
9. Cities will continue long-range planning excercises despite their empirical ineffectiveness.
10. Representative democracy will still exist (in U.S.) and local politics will still drive key decisions.

It’s more fun to predict what won’t be the same, but likely more critical to consider what will stand the test of time. What is something you believe will absolutely be true in cities in 10 years?

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What’s not going to change (in cities) in the next 10 years? was originally published in Better Planning on Medium, where people are continuing the conversation by highlighting and responding to this story.

What’s unique about pricing in govtech?

The visit-it-later pricing strategy is common for founders in all SaaS verticals. It’s much harder to take that approach in government for two reasons:

1. Government contracts are public record. This transparency means that other customers and your competitors have access to your pricing strategy at all times. This makes price changes, time discounts, cash discounts, and every other used car sales tactic much harder in this market. It’s a forcing function for price consistency and articulation. It doesn’t mean you can’t change pricing, it simply means changes in pricing need to be applied to the entire customer base, otherwise you envitably get the question; “why is that city paying less than me?” This puts an enormous amount of pressure on getting your initial pricing strategy more right than wrong. Pricing for government is much less iterative than say, pricing for SMBs. As we will see later, publicly available contracts can be beneficial for startups in the space when you determine your pricing strategy.
2. The number of customers in the govtech market is largely fixed. Most industries, especially enterprise SaaS and consumer SaaS have enormous turnover in their customer base. There are 550,000 new business started every month in the United States. That means, for an enterprise SaaS company, the customer base has new blood all of the time. The allows for companies to constantly test and iterate on their pricing models. In contrast, the number of cities and counties is around 22,000+/- and largely stays the same. Combine the stagnant number of potential customers with publicly-available contracts and the result is an environment much less than conducive to constant changes in price.

How should you price your product?

The price of your product is your signal to the world about how they should value your product. Overtime, price and value start to separate as the best products provide far more value than what they cost. However, at the moment of purchase, the price sets an expectation of value for the buyer. Buyers in all markets, but particularly in the govtech market, evaluate products on a relative basis. How does this product compare to what I am currently doing? How does the price of product A compare to the price of product B? If your price, and therefore the value signal you send, are arbitrarily determined you risk sending a signal that is incompatible with value.

In my experience, pricing your product for government boils down to four questions:

1. What is your product replacing and what’s the cost (direct or indirect) of the current solution?
2. How much agency is required to influence the buying process?
3. Is your product truly out-of-the box or does it require localization?
4. Once onboarded, can a customer self-serve or is a customer success representative required to extract full value from the product?

*These four questions must be answered together as they are very much interrelated.

What is your product replacing and what’s the cost (direct or indirect) of the current solution?
Many govtech products are replacing human workflows or consultant services. The answer to this question likely lies in publicly available information. If you’re replacing human workflows, you can generally get a sense of costs (i.e. salaries) for the people / roles performing that work in the agency. In the case of consulting services, the contracts, scope of work, and price are all available online. This information can serve as a guide to determine the existing costs for the “solution” your product provides.

The general rule of thumb for SaaS products is your product needs to be 10x better than the existing solution in order for your customers to justify abandoning the old solution and adopting your product. This 10x improvement can come in two forms; a)1/10 of the price of the existing solution or b)10x better output for the same price. I’ve found, for whatever reason, most startups tend to lean towards the former, charging less for a new product and attempting to win business on the basis of a lower price. Only you can determine if that’s the right pricing strategy, but I would caution companies to first explore what would need to be true if they charged the same amount and provided 10x the value.

How much agency is required to influence the buying process?
This is the question most companies overlook. Choose the statement that best describes the level of effort required to sell your product:

1. My product can be sold without any human intervention. ($10)
2. My product can be sold with minimal human intervention (chat-based sales support). ($100)
3. My product can be sold via web demo with no in-person meetings. ($1,000)
4. My product can be sold with a single in-person meeting. ($10,000)
5. My product can only be sold with several in-person meetings. ($100,000)

This is a question that requires govtech startups to be very honest with themselves. I find first-time govtech founders tend to think they will be able to sell their product with no in-person meetings, and end up severely underestimating the agency required to get a sale. This approach ends up being a double whammy. They price the procuct with that assumption in mind, end up doing several in person meetings to obtain the sale, and the result is unit economics that aren’t sustainable.

As you can see at the end of each statement, my rule of thumb is add a zero to your price with each subsequent level of effort. These statements represent effort, time, and often expertise required of your salesforce. Those factors will ultimately determine your cost of acquisition and whether or not you can endure as a business.

Is your product truly out-of-the box or does it require localization?
This is a question about level of effort for your customers to find value. Again, choose the statement that best describes your product:

1. My product is out-of-the-box and requires no localization.
2. My product requires minimal localization done by the customer.
3. My product requires some localization done by our team and some by the customer.
4. My product requires significant localization done by our team.
5. My product requires significant localization done by our team and the customer.

Generally speaking, anything that requires extra effort on behalf of the company, needs to be reflected in a price increase. A common example of this is set-up fees. While it’s uncommon, I personally believe the opposite should also be true. Anything that requires extra effort on behalf of the customer, should result in a price reduction. Let’s call this the anti set-up fee. If both parities are required to do work, this should also be considered in the form of time delay for the customer to extract value. A great example of not considering this is companies that sign 12-month agreements with customers and then require 4-months of set-up time, leaving themselves 2/3 of the contract term to actually provide value. This puts enormous downward pressure on customer success teams to deliver full value in a shorter period of time.

Not all govtech products require localization, however, anything involving the use of local data (parcels, permits, open data, etc..) almost always requires some degree of localization. Many enterprise SaaS companies push this localization onto the purchaser (i.e. salesforce pushes setup onto the buying company). Often times, government agencies don’t have the capacity or bandwidth to localize your product for their own use. In fact, many agencies are buying your product to avoid extra effort. In an industry dominated by consultants, requiring the agency to localize your product often feels like the thing you are trying to replace in the first place, human workflows.

Once onboarded, can a customer self-serve or is a customer success representative required to extract full value from the product?

The last factor to consider in determining price is the level of effort required to help your customer realize the value of the product. Again, the following statements represent a continuum of support:

1. My product is simple enough for a customer to onboard and use without assistance.
2. My product requires tool tips, but no human assistance.
3. My product requires human assistance, but only for onboarding.
4. My product requires monthly calls / meeting with customers + real-time help channels.
5. My product requires 24/7 support.

In my experience, I’ve seen two extremes play out in the govtech market when it comes to customer support. Companies either think their product doesn’t need support (when it does) or provide a suffocating amount of support (reducing the value of the actual product). Providing the right amount of customer support is often tricky and specific to a given product. The key here is understanding the cost structure of the required support and properly reflecting that in the initial price. Too many companies offer commodity pricing with a product that requires a ton of support, which puts them out over their skis on their unit economics. It’s almost always better to over-assume support needs early in a product lifecycle and price appropriately.

If there’s a single lesson from this post, it’s be intentional about your pricing strategy. Spend time on it just like you do your product strategy and sales strategy. Don’t let a lack of interest or curiosity about pricing be the reason you run out of cash just as your product is starting to find fit in the market.

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Pricing Your (SaaS) Product for Government was originally published in Better Planning on Medium, where people are continuing the conversation by highlighting and responding to this story.

De-identified location data can help answer key transportation questions — from a regional level all the way down to a city block.

Who uses the street, in what way, and why? These are common questions that planning agencies consider every day when trying to build better cities. The answers can help them see how well transit is connecting workers to jobs, explore the traffic impact of a new toll lane, or identify the need for bike lanes and wider sidewalks.

But standard planning tools can’t always answer these questions with complete or current details. Too often, planners must rely on costly household surveys conducted years ago or trip counters focused on a single transportation mode. Some agencies have complex modeling software, but that’s often limited by older data and an overly technical interface.

The result is an incomplete sense of city movement patterns and, consequently, a lower confidence in critical transportation and land use decisions.

There’s a key to unlocking better planning tools — right inside the smartphone you might be using to read this article. Our phones have a powerful location awareness that’s transforming many aspects of urban life: helping us get directions, avoid a traffic jam, find a restaurant, or hail a ride. But this type of location data hasn’t widely been used in the service of planning more equitable and adaptable cities.

We believe this powerful data source can help do just that. Meet Replica: a user-friendly modeling tool that uses de-identified mobile location data to give planning agencies a comprehensive portrait of how, when, and why people travel in urban areas.

Replica provides a full set of baseline travel measures that are very difficult to gather and maintain today, including the total number of people on a highway or local street network, what mode they’re using (car, transit, bike, or foot), and their trip purpose (commuting to work, going shopping, heading to school, etc). By updating these measures every three months, Replica also provides the ongoing ability to detect changes in these measures over time — helping planners answer questions about land use and transportation from a regional level all the way down to a city block.

Most importantly, Replica does all that with personal privacy built into its foundation.

A Virtual World With Real Qualities

There are many apps and companies that collect data about your location history and travel patterns via your smartphone. The problem is this data often contains personal information. Replica starts with data that has already been de-identified, meaning we never handle the original, identifiable information. We are not interested in the movement of individuals; we are interested in the collective movement of a particular place.

Replica uses this de-identified data from about 5 percent of the population to learn about travel patterns and create a travel behavior model — basically, a set of rules to represent who’s moving where, when, why, and how. But models aren’t perfect. So we gut check these rules using on-the-ground data (such as manual traffic counts or transit boardings) to make sure Replica is consistent with real-world movement patterns.

We then match these models with what planners often call a “synthetic” population. That’s a very technical term, but the basic idea is that planners can use incomplete samples of census demographic data to create a broad new data set that is statistically representative of the full population. The statistical process also removes any ability to identify a particular individual in the data. (We open-sourced this work last year and encourage others to examine our assumptions or build on top of them.)

When you combine travel behavior models with a representative population, you can confidently replicate trip patterns across a city or metro area.

In Replica, workers go to work and families go out to dinner. Roads are congested at rush hour, downtown sidewalks are busy at lunchtime, and bike paths are full after school. People travel in taxis, on foot, and in carpools. These movements are faithful to real-world activities but not traceable to actual people or specific trips. Planners can use this virtual world to help them make decisions about, and the study the impacts of, transportation or land use — without compromising individual privacy.

From “What Now” to “What If”

Let’s go back to the initial questions — who uses the street, in what way, and why — and consider them through the lens of a city planning agency that wants to make streets safer and friendlier to cyclists. Here’s a look at a Replica dashboard focused on a section of Main Street in Kansas City:

Understanding current conditions. The analysis above shows that nearly 14 percent of all trips in this corridor are made by cyclists and pedestrians, and while most of these people are commuting to work, a notable share are shopping. These baseline counts of trip mode and travel purpose are historically very difficult to gather, but they can help focus planning decisions around empirical evidence. For example, knowing that cyclists and pedestrians are shopping in this area might help demonstrate to local shop-owners that business won’t suffer if street-parking spaces are replaced with a bike lane.

Analyzing changes over time. Currently, there are still few cyclists in this area. But urbanists know that if a model (or, for that matter, a survey) tells you there aren’t many cyclists using a given street, that doesn’t mean people don’t want to bike there — they just might not feel safe enough. The ability to measure changes in usage patterns before and after implementing a bike lane could help planners demonstrate just how many more bike trips a new lane encouraged people to take, making it easier for local officials to support similar interventions elsewhere.

Guiding planning decisions. Over time, we plan to update Replica with the ability to explore prospective service changes and interventions — modeling the impact of Scenario A against Scenario B. We believe this capability can help local officials make the most of limited funding and physical space. It can also help them engage the public around planning decisions in a clearer way. As we’ve written before, transparent models can become the basis for community workshops around things like inclusive street design, helping planners explain the impact that various options might have on different populations.

We are currently building Replica to support the development of plans for Sidewalk Toronto. One of that project’s core objectives is to give communities new tools to adapt much more quickly than cities can today, and we believe Replica can not only help us explore new ideas but to communicate their potential impact to a wider public. As part of this process, we’ll be sharing Replica with local Toronto researchers and public agencies to gather feedback and make it more useful to them.

Later this year, Replica will make its U.S. debut in the Kansas City and Chicago regions, with other areas to follow.

We know models don’t provide simple solutions to planning problems. They’re tools — albeit ones we believe can be more accurate and useful than existing tools. Planning decisions still must reflect the priorities and values of the local community. And many factors beyond modeling outcomes go into urban planning decisions.

But as one Kansas City planner told us during the development of Replica: “The more detail you give me, the more questions I can answer.” By giving planning agencies information that’s more accurate, current, and representative than what’s typically available, we can help them respond more quickly to their community’s needs today — and prepare for the future.

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Introducing Replica, a next-generation urban planning tool was originally published in Sidewalk Talk on Medium, where people are continuing the conversation by highlighting and responding to this story.

I’ve spent my entire career either working in local government or working with local governments. I have a degree in urban planning. I own a home. I have kids. I vote in every election. And, as a part of my professional life, I regularly meet with city officials. On paper, I possess a near ideal set of attributes for the type of person cities would expect to provide feedback. Yet, I don’t attend public meetings and rarely, if ever, provide feedback online.

Statistically speaking, I’m not alone. We’ve all heard the dire stats around civic engagement — only 10% of people go to more than one public meeting a year. This general lack of engagement is a bit strange if you consider the resources dedicated to engaging local citizens. Every government agency has dozens (if not hundreds) of public meetings a year. Almost every agency provides an opportunity for digital engagement. Additionally, almost every agency hires consultants to help market and facilitate these events. If all of this time and money isn’t generating better results, aren’t we obligated to consider alternatives?

Community engagement has an incentive problem

Why do people get involved in local affairs? What incentive do they have to show up to that public meeting? In my experience, it generally boils down to three things:

1. The topic at hand is, or perceived to be, particularly impactful to their time, wallet, kids, or values.
2. The topic at hand is particularly controversial or marketed as such.
3. They have a lot of free time.

We like to think the mental calculus for getting involved in our local communities is different than everyday decisions, but, it’s really not. We make decisions based on expected benefits outweighing the expected cost. It doesn’t mean we act rationally (in the purest economic sense), but we do act in ways that we believe to be beneficial to us or our value set. This — understanding what drives behavior — is largely overlooked when it comes to community involvement.

How do we solve the incentive problem?

Tangible incentives. In other words, pay people. Stay with me here. Imagine for a second, the reasons people might get involved now looked like this:

1. The topic at hand is, or perceived to be, particularly impactful to their time, wallet, kids, or values.
2. The topic at hand is particularly controversial or marketed as such.
3. They have a lot of free time.
4. They get paid.

Paying people for their time and input isn’t a new concept. People get paid for doing consumer and market research all of the time. It’s widely accepted by both the companies conducting the research and the participants providing information. It’s done online. It’s done in-person. In fact, these things pay really well…up to $140 / hour.

For whatever reason, community engagement is shrouded in expectations of community altruism, otherwise known as “civic duty.”

The ole civic duty argument goes something like this; “We shouldn’t have to pay people to get involved in their own community…it’s their civic duty.” That’s a straw man argument. If we followed that logic through, we surely wouldn’t need to pay the local consultant to help plan and facilitate the meeting. We surely wouldn’t need to pay the product company providing digital engagement tools. But we do pay consultants and product companies for their time . We pay them well in fact.

Government agencies have rightly determined that doing engagement cost time and money. Today, that money flows to 3rd parties — consultants and products — who then provide some platform for the engagement to occur. To be clear, the payment is for a platform, either a physical meeting or digital tool, to help facilitate the engagement that occurs. Only a small percentage, if any, of the payment is applied to participant acquisition.

Show your citizens the money

What if, instead of paying a consultant or product company $100,000 for a single project(!), we just paid participants to show up and provide feedback? No different than a consumer marketing company, we could pay participants based on a variety of factors. We could pay based on time (hourly rate), expertise, or willingness to share additional personal information (demographic data). In effect, let’s take the resources already allocated for engagement and let them flow directly into participant pockets.

This kind of approach would need to be thoughtful, well planned, and adaptable. Not every project has the same engagement needs. Some projects require a high volume of participation, others require deep expertise, and others require a statistically significant sample. The pay-for-participation model allows us to tweak the incentives to ensure each project incentivizes the right kind of engagement. And of course, anyone that wants to invoke their civic duty can gladly refuse or donate their payment.

Still skeptical? What’s the worst that could happen? I suspect the worst isn’t actually worse than the current state of affairs; empty meeting rooms with well-paid consultants. I do believe a model like this has the potential to radically change the demographics of participation, provide feedback that is far more representative, and in the process, help a larger number of people become more informed about the cities in which they reside.

If you know of a pay-for-participation experiment that has been tried, please let me know.

Interested in getting a curated selection of the two most important things to read in #govtech every few weeks? Sign up here.

Pay people to attend public meetings was originally published in Better Planning on Medium, where people are continuing the conversation by highlighting and responding to this story.

Just a decade ago, gov tech was an industry dominated by large, legacy vendors. Many of the “solutions” at that time were still being delivered by CD through the mail and downloaded onto a local machine. The cloud and software as a service were foreign concepts. Most important, the very best talent had little to no interest in working in an industry that was seen as boring, slow and unwilling to evolve. Times have changed.

Today, dare I say it, gov tech is even exciting. It’s become both admirable and cool to build products that improve government operations, increase civic awareness, and attempt to solve some of society’s biggest problems. The last decade has produced a number of great SaaS companies, significant investment, federal support (United States Digital Service, 18F), and an ever-growing volunteer/hacking community. Government has officially joined the 21st century.

All of this progress has been great and should be recognized. There’s much more work to be done. In fact, the most tantalizing prospect in this industry lies mostly untouched: an UrbanOS.

The core responsibility of any city is to facilitate diverse and rewarding interactions between people and the physical environment. When we think about the places we love — the places we want to live and visit — we never cite the formal governing body as a primary reason. I surely wouldn’t say, “Wow, I really want to live in New York because the city and its wonderful workers are so great.” It’s more likely I would say, “SoHo is such a great neighborhood, the shops and architecture and people are amazing.” Of course we know that the city and its wonderful workers do in fact play a key role in delivering a great experience. Cities are the mechanisms by which we deliver memorable experiences through stimulating physical and social environments.

The memorable experiences we have in cities are a manifestation of every city operation working well together. The efficient movement of people and goods, thoughtful public spaces, the right scale and density, quality urban design, and a sustaining economic environment are all contributing factors. Done well, these attract and retain diverse people, who further enhance and improve the physical environment. This positively reinforcing flywheel propels more growth, thus leading to more and better experiences.

The formal governing body (“The City”) is the operating system through which all of this is possible. It determines, through laws and regulations, what is permitted in any given place. In the pre-digital era, the efficiency of the operating system was highly dependent on a number of people being in constant collaboration. Government is no longer in the pre-digital era. The explosion of new apps and products to service the specific needs of the system will continue to be important; however, at this moment, these technologies operate independently at best and in conflict at worst. Each of these products might be improving an isolated workflow, but the sum of the disconnected parts is likely making the whole operate much less efficiently.

It’s time for an UrbanOS. A modern, digital version of the human operating system that enables a sum greater than the parts. The goal for this industry shouldn’t be simply to build technology for government and its citizens. The goal should be to use technology to facilitate more memorable moments. To make the interactions between the physical and social worlds even better. To enable and empower a citizen experience that is modern and equitable. In order for this to occur, someone, some organization must thoughtfully pursue the idea that these technologies can and should work together to make the places we live the best they can possibly be.

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It’s time for an UrbanOS was originally published in Better Planning on Medium, where people are continuing the conversation by highlighting and responding to this story.

I’m excited to see what 2018 brings, Happy New Year!

Interested in getting a curated selection of the two most important things to read in #govtech every two weeks? Sign up here.

Looking Ahead: GovTech Predictions for 2018 was originally published in Better Planning on Medium, where people are continuing the conversation by highlighting and responding to this story.

• Participation — a high share of people in the city choose to engage in some way. They recognize that it is important and worthwhile to engage with the city.
• Responsiveness — there is a reasonable level of responsiveness inherent in the program design. This includes acknowledgement of response to when there are problems, they are flagged and fixed.
• Representation — the voice represented in citizen feedback or democratic decision-making are representative of the population as a whole. They are not concentrated among those with money, time, and education. They are all-inclusive.

Civic engagement’s practitioners and products, mindful of these objectives, have made a number of attempts to improve the results over the years. While the era of smart phones, open data, and smart cities hyperbolically promised to solve our citizen engagement woes, the state of affairs is much the same:

1. The predominant method for citizen engagement still happens to be the classic town hall event. The town hall has seen some slight adaptations with the introduction of charrettes and various participatory tactics, however, the essence — going to a specific time at a specific place — still holds true.
2. The people who engage in local affairs are typically unrepresentative of the population as a whole. They are “power users” and contributors whereas the voices of people without the time, the education, or the resources to participate often go unheard.

To date, attempts at using technology for engagement have simply followed the rational choice model; if we reduce the time and cost for people to get involved, the result will be more involvement. This simplistic view of the world ignores two very important factors; (1) humans aren’t rational, and (2) technology is subject to the same constraints of the real world, notably time, cost, and access. Both of these factors appear to be having a significant impact on meaningful improvement when it comes to civic engagement efforts.

As we know, humans have a set of psychological tendencies that make them behave quite irrationally. In many ways, new technologies and products have only enhanced these tendencies. We’re:

• Default-prone
• Loss-averse
• Routine-oriented
• Status-driven

How is this relevant to civic engagement? We see these factors present themselves in a myriad of ways. The following are a set of hypothesis formed through years of practice, observation, and research as to why efforts in civic engagement continue to produce lackluster results.

Hypothesis #1: An individual’s willingness to engage in local community affairs likely follows a form of the exploit-explore continuum.

Our tendencies to be both default-prone and routine-oriented mean we quickly assimilate to a personalized version of community — my house, my street, my neighborhood — and then move into exploit mode. In doing so, we reduce risk, protect our investments (i.e. home value), and largely fall into routines. There are a small number of life changes that disrupt this routine and put us back into explore mode:

• Moving to a new place
• Buying a home
• Having a child
• Children moving out of the home
• Death of a partner

The implication here is that individuals often approach civic engagement as a way of solving problems applicable to their version of community. It is challenging — in the absence of these disruptive events — to prompt individuals to engage civically beyond the issues directly relevant to their house, street, and neighborhood.

Hypothesis #2: Participation in local community affairs depends strongly on the ease with which citizens can learn about a particular program and sign-up.

Like any voluntary activity, citizen engagement faces a number of barriers. These include things like time, access, trust in government, agency responsiveness, cultural misunderstandings, and opportunity costs. Most notably, civic engagement is generally presented as a high effort / high time activity. The lack of easy on and off-ramps into local engagement is quite stunning. Even government benefits such as Obamacare and Food Stamps have had a difficult time of getting people to enroll in free services. The success of CalFresh, a food stamps enrollment program, can be instructive for improving participation more broadly.

Hypothesis #3: Engagement processes and products aren’t designed to tap into a diversified set of interest and expertise in any given community.

If shouldn’t come as a surprise, but citizens have varying degrees of interest and competencies when it comes contributing to an engagement process. Programs and products actually cater to and promote power user behavior and interest, unintentionally rewarding people with the most time. Technology doesn’t change this, contrary to popular belief. The world is complicated and citizens shouldn’t be expected to have the expertise to make anything close to optimal decisions in all of the domains of their local community. Engagement programs and products should be designed to allow people to contribute across time and interest spectrums.

Hypothesis #4: Successful engagement programs (as measured by the number of people involved) have diseconomies of scale.

As an engagement program moves beyond the power users and always involved, it experiences a similar problem to last-mile shipping costs. The drag forces on sharing information and involving the traditionally uninvolved increase substantially, thus resulting in more energy and resources on a per participant basis. In the event that a program does involve more people, the increased inputs (people, ideas, comments, etc…) create more work for the sponsor to be properly responsive. These diseconomies of scale are often either not considered at all or not understood until the budgets been used.

A New Framework

In order to overcome some of these issues, engagement programs need to consider a new conceptual framework. Too many engagement programs are a series of independent tactics (i.e. meetings, surveys, etc..) without consideration for how and why people participate. A channel-driven framework, might look something like:

• Passive Engagement: Efforts where data is collected from citizens as a part of their routine and non-routine interactions with the city, both the governing body and physical environment. Cities are effectively machines for generating continuous feedback. Residents are constantly interacting with city services and infrastructure, providing a constant stream of information about preferences, destinations, and place-based behaviors. Engagement programs can and should be designing transparent solutions to take advantage of this information and in turn presenting the findings back to residents as a set of baseline conditions.
• Active Engagement: Efforts where citizens go out and invest the energy to make their voices heard. Town hall meetings and idea collection technologies can and should have a place in the process. We simply need to understand that these methods do and will always require energy and effort from citizens. Active engagement efforts should also start exploring the use of AR / VR as ways to provide experiential opportunities for residents. Establishing permanent brick-and-mortar locations for citizen feedback, appreciation, or grievance should also be considered. We shouldn’t need a “project” in order to be active members of the community.
• Hybrid Engagement: Efforts where citizens are intercepted within their routines and given an opportunity to provide feedback. A current tactic that falls into this category is transit rider surveys, that take place while people get on and off or ride transit. This kind of intercepting can include much more than surveys and often times can provide both appropriate context (feedback on transit while riding transit) and time (transit time) for people to participate meaningfully.

Open to Being Wrong

I thought I was done with civic engagement a long time ago, in the professional sense at least. As I watched govtech and civictech grow, it feels like civic engagement has largely been forgotten and even in some circles it’s considered a “has-been” problem. I don’t think thats true and hope that someone or some organization is willing to take some risks and push it to what it can become. If you have examples of engagement done well, please do send an email to nick (at) betterplanning.co.

*Special thanks to Ben Armstrong at MIT for his contributions, feedback, and continued interest in this space.

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Civic Engagement is still broken — and a huge opportunity. was originally published in Better Planning on Medium, where people are continuing the conversation by highlighting and responding to this story.

The potential outcomes are tantalizing:

• Recognition from one of the most respected and innovative companies in the world that your city is where they want to locate a second headquarters.
• 50,000 high quality, well-paid jobs.
• Some multiple of supporting jobs in retail (ironic), restaurants, and ancillary services.
• Significant infrastructure upgrades, with a likely emphasis on transit and alternative transportation.
• A beautiful corporate campus that serves as an anchor of business activity.

Talk about legacy-making stuff for an elected official. Every city should absolutely desire these outcomes, but at what cost? Second, and equally important, why did it take an RFP from Amazon to spur cities into these kinds of discussions?

What’s it all worth?

For those people who say the incentives are just the cost of doing business in this situation, I say, $10B is just the cost of doing business? Early estimates, based on recent incentive packages for GE, Apple, Facebook, and FoxConn, project this deal could command between $9-$11.5 billion incentive packages. That’s everything from land to infrastructure to tax abatement. That’s simply the incentive package, the price of admission. That doesn’t include any ongoing costs associated with all of the new infrastructure required. Notably, and one detail often not mentioned, deals that include tax abatement can negatively impact public school districts who rely on local taxes for funding.

And what about the cost of time? Presumably, 100 or so cities will spin their wheels and crank out responses to the RFP. This effort will include all kinds of creative accounting and justification and involve the most important people inside of these agencies, for an extended period of time. Cities are in the business of RFPs, so they should know better than anyone, if you find out about an RFP that day it’s released, you’ve got no chance at winning. That’s not how these things work. It’s inconceivable that Amazon hasn’t already spoken with the small number of places it’s interested in locating HQ2. No one, particularly a private company that has a history of being relentless in the pursuit of efficiency, wants to go through an RFP process.

A natural conclusion one might draw is that Amazon want to ensure that their preferred location(s) are truly providing the very best offer. There’s not better way to find out than creating a heralded competition between cities. Wouldn’t it be fascinating, in the spirit of open data, if every submission was public? Imagine if every elected official and city leader knew that the enormous package they were offering was going to be seen by everyone; competing cities and their local residents. How might that change the response?

What’s the alternative?

Powerball jackpots are certainly one way to build wealth, however, I don’t know of many people whose primary strategy for obtaining wealth is buying Powerball tickets. Games of chance, particularly ones with very long odds, are generally met with proportionate effort. When that once-in-a-lifetime jackpot presents itself, we might buy a ticket, but we don’t abandon the plan we have in place. All of this Amazon hoopla got me thinking, do cities have explicit plans for adding 50,000 jobs over the next 20 years? Yeah yeah, I know every city wants to add jobs and every city has plans. What I am talking about is an explicit plan, that has all of the effort and energy and incentives cities are willing to give to Amazon, but dedicated to home-growing the same outcomes.

Thinking about adding 50,000 jobs is too hard to fathom. Let’s break it down to something easier to understand. What if one of these cities, instead of responding to the Amazon RFP, took that $10B and applied it to home-growing 1,000 new companies with 50 employees each? That would yield many of the same outcomes, but feels more like a day job and less like a Powerball ticket. In effect, we (city) are committed to enabling and retaining the next Amazon instead of racing to the bottom for the current Amazon.

I know a ton of startups that would accept any or all of the following benefits:

• Free land or office space
• Free or nearly free utilities
• Free and improved infrastructure, like transit and bike lanes
• No local or state employee taxes

I’d also being willing to bet that any city who said, we will do whatever it takes to enable and recruit any company who has aspirations of starting or growing to 50 employees over the next 20 years, would generate sufficient press and likely have a flood of interest. I get it, building things from the ground up, particularly things that take a generation or more is hard. Comparatively, responding to an RFP (even when you know you can’t win) is really easy.

Just like Powerball, there will only be one lucky HQ2 winner. For the rest of you cities, what’s that wealth-building day job going to look like?

Cities are approaching this Amazon RFP all wrong was originally published in Better Planning on Medium, where people are continuing the conversation by highlighting and responding to this story.

True Cost of a Product = Product Price + Time Spent

As a company, you need to thoroughly appreciate the switching costs your customers will endure. It’s one of the biggest contributors, often times implicitly, in why people choose to buy or pass on your product. Remember, the entire govtech industry is better off when new products are successfully implemented — agencies gain confidence in upgrading to new software, they believe startups can actually serve their needs, and companies grow through increased demand.

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The Business of GovTech: Switching Costs was originally published in Better Planning on Medium, where people are continuing the conversation by highlighting and responding to this story.

To be clear, I’m pro measurement. I think the operational side of government would benefit greatly from more frequent and easier measurement. There are numerous benefits to proper measurement systems. Most notably, people and organizations play different when they are keeping score. Measurement has the ability to create positive feedback loops, thus reinforcing good decisions and enabling us to see the impacts of poor decisions.

Government agencies should be serious about increasing their business intelligence capacity. The first step in that process is better data collection and acquisition. If you can’t collect it, take the money you were going to spend on a dashboard and go acquire differentiated, local data. Getting better data is 100x more important than creating dashboards or analyzing census data.

The second step in that process is understanding the relationship (and difference) between goals, lead measures, and lag measures. Much of the work done to date in government dashboarding fails to recognize this difference. A goal is a desired result. A goal is specific and if achieved will return tangible and substantial benefits to the city. Lead measures are near-future events that you control that have an impact on long-term goals. Lag measures are things you are ultimately trying to improve. Census data, as an example, can only ever be used as a lag measure. It’s frequency and precision doesn’t allow it to be used as a lead measure.

Building dashboards (or the like) that only show lag measures, and even worse, project them as goals can and will cause a variety of misinformed strategies and tactics. A dashboard, or any other visualization method, should properly highlight the purpose of each measurement. In a perfect world, the visualization actually keeps the family of measurements together. Here are two simple examples of this structure in context:

Goal: Increase taxable value of land in downtown

Lead Measure: New building permits on underutilized land

Lag Measure: Annual property valuations

Goal: Increase alternative transportation mode share

Lead Measure: Mode share changes during temporarily road closures

Lag Measure: Decennial Census mode share

The problem isn’t government agencies wanting to measure more things or companies wanting to provide a service to assist in that effort. The problem is “dashboards” and other visualization tools have somehow become synonymous with “business intelligence” and “better decision-making.” Dashboards are only visualization tool. They’re a pure commodity. Dashboards with undifferentiated data are an undifferentiated product, something that can and should be done in house.

It’s possible, once we’ve collected better data and structured the purpose of our efforts properly, that a dashboard or another visualization technique may be a great way to share and monitor those efforts. Until then, stop the madness.

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Please. No More Dashboards. was originally published in Better Planning on Medium, where people are continuing the conversation by highlighting and responding to this story.