Blockchaining the Smart City

While my previous blogs have focused on Smart City initiatives that have proven their relevance and effectiveness through implementations worldwide, I am testing unknown waters through this latest blog and attempting a leap into the future by bringing Blockchain to the Smart city context.

Blockchain technology has been around for some time and has gained popularity in its “bitcoin” avatar, but there has been recent interest across multiple industries to leverage it in their business context. Blockchain, in simple words, is based on a shared ledger technology allowing any participant in the business network to see the system of record. It has the potential of disrupting legacy operations and is evolving at a rather brisk pace. The financial services industry has been at the forefront of Blockchain adoption with its most important attributes – “security, transparency, indelibility and trust” – aligning naturally with their business operations. However, there are many other industries like logistics, travel and transport, legal services, government that are donning their thinking hats and ideating around this innovative technology.

This blog puts together a view of a potential set of use cases from the Smart Cities operational context that I believe are well suited for adopting Blockchain technology and deliver an enhanced experience to its residents. These are early days though, and these ideas do not necessarily have a precedent to assure a successful outcome. However, a Smart City is an ecosystem by itself and this blog provides a futuristic Point-of-View to identify how this ecosystem could benefit from Blockchain technology.

Before delving into further details, I believe a classification of the Smart Cities landscape is essential to map Blockchain initiatives accordingly. Not every initiative can be applied to every Smart City out there. Some of the initiatives are better driven by Government while there are a few that better suit Private ownership. So, the broad classification and a point of view of the initiatives that map to them are represented in the graphic below. The categorization of initiatives is not cast in stone but indicative of where I believe the initiative maps the closest.

The overlap between the X and Y axes in the 2*2 quadrant captures the relevant initiatives. For example, Public Owned Brownfield Smart Cities would gain immensely from leveraging Blockchain technology to deliver Social Services benefits while this is not the case with the Private Owned Smart Cities.

Let us get into these Blockchain applications in further detail:

• Smart Payments – As mentioned earlier, Blockchain technology has its roots in the Finance industry and has found early adopters in banks worldwide. In fact, Banks are now racing to harness the power of the Blockchain technology with a strong focus on e-payments and money transfers. Once the technology is proven, these can be implemented in a Smart city environment to execute utility bill payments, wallet-enabled transactions, payment of fines etc in a secure and transparent manner for its residents. This eases the life of the Smart City residents while assuring them that every fund transfer is being permanently recorded.
• Smart Land Records – Blockchain technology lends itself perfectly to help overcome property frauds by preventing or reducing it. The underlying reason for Blockchain to have gained in credibility is the indelible nature of its distributed ledger and transparency that comes with the ledger. Property prices have been on an upward swing worldwide and there are many fraudsters who are making most of the hype cycle by dubiously creating ownership records and disappearing as soon as they have made their money. These instances can be taken out of the system effectively and efficiently if every single transaction associated with a property is recorded in permanent ink, a.k.a Blockchain ledger. Smart cities, both private and government owned, can leverage the technology to establish a property management system that ensures peace of mind to all city stakeholders.
• Social Service benefits delivery – Most countries provide social service benefits to its citizens based on their socio-economic position in the society. The intent of these benefits is to result in upliftment of the society at large. However, there are umpteen instances when middlemen do not let these benefits reach the actual recipient by exploiting loopholes in the supply chain. The centralized nature of a Blockchain where everything can be tracked by the central authority will make it challenging, if not impossible, to fool the system thereby ensuring that all social benefits reach the intended recipients and all leakages are plugged. A smart city needs to accommodate every strata of society and join hands with the larger Government machinery to implement such a Blockchain-based initiative will be ideal in most of the developing world.
• Tax collection – The distributed ledger of Blockchain has the potential to help government in tax collections. As governments are making attempts to establish a simple tax system that places accountability on the individual/company to pay tax impromptu rather than charging them retrospectively, they could find their answer in Blockchain’s real-time, secure and reliable execution and recording of transactions. This results in plugging revenue leakages and provide data that is reliable both for taxpayers and tax authorities. For example, in India there is a push for tax reforms through the proposed GST policy that will establish comprehensive indirect tax on manufacture, sale and consumption of goods and services throughout India. Taxable goods and services are taxed at a single rate in a supply chain till the goods or services reach the consumer. This lends itself beautifully to track tax paid all along the supply chain using the reliable Blockchain technology.
• Smart Voting – Blockchain has found a rather unusual use in enabling transparent and reliable e-voting. While most countries have adopted various technologies over the years to improve voter percentages, e-voting adoption has yet to take off meaningfully worldwide. There are concerns that existing platforms are vulnerable to fraud, corruption and sabotage. It is to solve this challenge that Blockchain technology is being used to deliver convenience to the voters while ensuring security and reducing voting fraud. As mentioned earlier, Smart Cities are ecosystems by themselves and can use such Blockchain technology based voting systems to encourage participation in local elections (Example – Smart City Governance Boards) within the Smart city’s purview – delivering a signature city experience through effective and efficient resident engagement.
• Smart Transportation – Residents of almost every city in the world face transportation challenges today . The urban dweller looks for the convenience of moving from Point A to Point B with least hassle. It is this need that cab aggregators like Uber have tapped into and have a business model that is widely successful. However, what has also been irking some customers is the “centralized” nature of their operations with one HQ governing their operations worldwide. In response to this, Arcade City launched an innovative operating model being built on Blockchain technology in September 2016 that will decentralize the operations and provide lot more authority and decision making capability to the driver, who is the all-important “touchpoint” to the customer. The coming months will tell if this stands a chance of being disruptive. A Smart city can take this a step further and implement all transport services across various modes within the city – school buses could implement Blockchain-based identity, 3PL service providers could leverage it to make their supply chain more effective, public transport could be made more accurate and reliable etc. and innovations like the Arcade City initiative could provide alternates to move around that truly differentiate the city from the rest.

While these initiatives are futuristic in nature, the pace of innovations today is swifter than ever before. There are a number of Smart City initiatives being taken up worldwide and it is all about delivering a “differentiated signature city experience”. Towards this end, Blockchain technology and innovations around it could provide an alternate worth exploring. With all the hype also comes a word of caution – do not underestimate the technical and organizational challenges of building and adopting Blockchain-based systems. In summary, a pragmatic and thoroughly thought-through approach is suggested.

Making Informed Decisions within Government

Through my previous blogs, I have emphasized consistently on the significant value that lies within the data housed in various government systems and records. While there is significant in-house data, a small fraction of the possible value is being realized today. So, the progressive journey that I had shared in an earlier post and illustrated below again provides a practical staged transformation approach that governments can adopt.

This transformation towards the establishment of an Open Data Platform not only drives ease of operations within Government but also promotes innovation from the larger ecosystem. This can be achieved by encouraging participation of Private Entities and General Public to tap into the Government datasets and thereby, creating citizen/resident experiences that would have otherwise been impossible, considering the limited resources at Government’s disposal. While this scenario considers the value that external stakeholders can generate by leveraging Government data along with non-Government data, the converse of this scenario will be the focus of this blog.

The converse is this –

• Government is not the data provider but it is the data consumer
• External stakeholders (Private entities, Citizens, Third parties) are not data consumers but are data providers
• Government taps into the value of Government data + Non-government data

The illustration below extrapolates the 3-stage transformation journey and appends a fourth stage that I call the “Analytics-driven Decision making Platform (ADDP)”. This ADDP can, and ideally should, co-exist with the Stage 3 of the transformation journey, viz the Open Data Platform (ODP). The idea is for the government to tap into its in-house data and correlate that with public data that is available to it (Open Data) and generate value through analytics on the integrated whole. The public data that can be brought on this platform include Quarterly/Annual filings by firms and individuals to Social feeds by residents/citizens/visitors about government services, weather data, media reports etc. Since the in-house data is not going out of Government boundaries, the concerns around data privacy and security are no longer relevant. Such a platform encourages government employees to innovatively think of ways to tap into the data from the larger ecosystem and leverage the same to deliver efficient and effective operations and more importantly, a positive people experience. So, they are not just doing the mundane daily routine but are being given an opportunity to be innovative and push their boundaries – something that you would rarely associate with government employees. Of course, this requires a cultural shift that needs to happen alongside the commissioning of ADDP.

The most significant value of an ADDP initiative is using the analytics to make informed policy decisions and also drive course corrections in real-time. A business scenario of such a platform has been depicted below.

The scenario shows Data at Rest (Historical data sitting in the Databases, Datawarehouses etc) and Data in Motion (Real-time data about events, incidents, status) from different entities like Government, Corporate, Citizens, Media houses, Weather etc. It is obvious that if this broad spectrum of incoming data has to staged on the ADDP, one has to be considerate of the Four Vs of data – Volume, Velocity, Variety and Veracity. The platform should be able to gather data that is unstructured or structured, real-time or static, machine readable or non-machine readable, clean or nonsensical and from thereon identify data that is relevant in a certain government context. This needs to be facilitated by a reliable Big data platform with strong analytical capabilities.

Here’s an example – Imagine that the Ministry of Education wants to make a decision  whether the subsidized education scheme that has been operational for last 3 years should be continued from the coming financial year onwards. Traditionally, this would be done by tapping into Government’s historical records to see the success and outreach of the scheme in terms of its adoption rate across the country. While this is an important parameter, combine this with

(a) what the citizens or the school administrations have been saying about this scheme on social media

(b) what the media houses have been writing about it

(c) correlate that with improvement in employ-ability rates that has been tracked by the Ministry of Labor studies and

(d) correlate that with financial burden on the exchequer tracked by the Ministry of Finance

(e) combined with what the UNESCO publishes in its “Global Education Digest” report about the status of child education in the country

Such aggregation of datasets from various sources gives a holistic view that can then be analyzed by drawing correlations between various perspectives and provide insights that would otherwise be unavailable. The Government, viz their internal workforce, should be entrusted with the responsibility to identify the nature of datasets that are required to achieve the comprehensive picture. The government employees are best positioned to identify the lacunae in existing information and with the ADDP platform, the get a rare opportunity to be creative and innovate.

Between Stage 3 (ODP) and Stage 4 (ADDP), governments would ideally want to adopt the ODP approach first but there is no stringent requirement to do so. So, while it is not absolutely necessary to have ODP and ADDP done in a sequential manner, these initiatives are complementary and should ideally co-exist. Each of the four stages of the transformation journey brings unique value as they are realized.

It must be noted that governments worldwide are yet to reach this stage of informed decision making through a data platform. However, in this age where gigabytes of data are generated at the wink of an eye, there is immense potential in such a platform. While ODP initiatives has been picking up steam worldwide and are widely published and talked about, there are very limited initiatives to establish an ADDP and the known few are in their nascent stages.

This ADDP stage requires a huge transformational shift internally but the incentive to get there is unprecedented.
Note: I presented on the topic of Open Government Data at a conference held by The Open Group in Feb 2016. This presentation summarizes the posts from my blogsite.

I’ve opened my Government data – What next?

In my previous blog, I published my views about how governments can (and should) conduct due diligence in identifying the relevant datasets from their blackbox databases and open them up. This included identifying attributes of open data and mapping the data to a 5-star rating. Having touched on the significant potential that Open Government Data holds in the evolution of the Smart City ecosystem, I paused my thoughts with a question –

Is the Open Government Data story complete once government entities have made data available in 5-star format (the best possible format)? Or would you say the story has only started on a strong footing?

The answer to that question is fairly obvious to anyone who understands the Supply-Demand equation of any transaction – . However, what is important to note in the Open Government Data context is that the demand side of the equation involves substantial dynamics. There are 2 very critical aspects of demand – drive consumption and, more importantly, drive value-generation from open government data. The illustration below captures this journey succinctly.

 

The rest of this blog will detail what it takes to drive the consumption story for open government data.

Driving Data Consumption

In a simplistic view, all this requires is for government entities to make a few commitments and honor them at all times.

• Commitment to provide fresh data at all times
• Commitment to bind the data service with a Service Level Agreement (SLA)
• Commitment to maintain data quality at all times
• Commitment to ensure data anonymity

The key to data consumption is to provide the Data Consumer sufficient evidence to instill trust in the relationship. As is observed with any relationship, an honored commitment is the best way to drive this. Hence, it becomes essential for Data Provider agencies to step lock with consumers at all times. One of the key concerns most consumers have is the governments usually are high-handed and set the rules of the game. Here is a scenario – A flourishing start-up has built a rich mobile app and open API for a service that brings together datasets from 3 different government agencies and combines that with data gathered from 2 other private entities. The app sources government data from an open data portal hosted by the government. The app has been in the market for about a year and has seen a good uptake because of the uniqueness of the service it offers. The start-up has been making healthy revenues through the mobile app and the open API that renders this service. One of the government agencies has done an internal study and has put in a regulation which restricts the contours of data that is shared outside the government. Following this, what if the agency decides that –

• A certain dataset that was being used by the start-up will not be made available from the next quarter
• The dataset refresh will be done only once every quarter instead of monthly
• The nature/quality of data shared will change from the next refresh onwards
• The dataset access will be blocked completely with immediate effect

The flourishing start-up will have no choice but to rework their innovative service around these new changes, provided that is feasible and practical. Unlike a B2B relationship where both parties have almost equal say, a G2B relationship is steered by one party – the Government.

It is to be recognized that the lack of transparency has an adverse impact on the public trust in the objectives and motives of the government. Open Data consumption is not a one-time task but a continual process that requires objective commitment levels from the data source entity over an extended period of time to gain the confidence of data consumers. It is time Governments get the balance right in the G2B relationship – as an example, they should come out with clear SLAs that govern the relationship. This is a common practice in any B2B and B2C relationships.

Another area that the governments need to work on is to influence and create the perception that they are doing enough to protect individuals’ rights to privacy and confidentiality of the data held by them. The last thing a data consumer would want is to be entangled in legal issues because the data was not anonymized¹ or pseudonymised² adequately/accurately at the source. Governments should be able to confidently state that the data is anonymized to an extent that it rules out any chances of a reconstruction through the Mosaic Effect³.

Generating value from Open Data

Once the trust between the Data Source entities and Data consumers has been established, it is mostly up to the data consumers to tap into the data and generate value that was unseen for various reasons. More often, the value generation comes from the fact that the data consumers are able to correlate various datasets – government data, private data, and proprietary data – and render use cases that wouldn’t be possible otherwise. Having said that, the governments can still play a substantial role to positively influence the larger ecosystem.

As an example, in one of my earlier posts I had mentioned about the 5-star rating by Tim Berners Lee. One of the key aspects of open government data – ranging from 1-star to 5-star – is that the data consumer agency should be able to further license the data without restrictions on use as part of the public domain. Public data should be released such that it enables free re-use, including commercial re-use. The possibility to distribute data without restrictions will encourage consumption and generate new avenues in the city ecosystem to leverage the intrinsic value of open government data. This will spur further innovation.

Another way that Governments can play an active role in encouraging the community to innovate based on open data is by ensuring that datasets of real value are being made available. While the government may have thought through the data that can be opened up, it is only at the consumption stage that the lacunae in the nature or quality of data becomes apparent. Governments should establish a mechanism by which the consumers can submit their concerns about existing datasets or place requests for more relevant datasets. The government will be able to know the pulse of the consumer community only when such a closed loop exists. At the end of the day, the value of open government data is only realized when then data consumers can generate experiences (through mobile apps, open APIs et al) that enhance the living experience of the residents.

In conclusion, Governments have an active role to play all through the Open Data journey – from data identification to value-generation. Most governments consider their job done once the data is made available on the Open Data platform. As mentioned above, that is just half the job and will serve a minimal purpose without a focus on data consumption side. With large initiatives of this nature, it is essential to keep receiving encouraging signs for the government entities to stay engaged and for the Open Data initiative to sustain over a long tenure. Hence, it becomes essential to ensure that the data consumers are also constantly engaged and their expectations are reasonably met. The need is to establish an ecosystem where all stakeholders participate and play their role towards delivering an enhanced living experience.

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¹Anonymised Data – Data relating to a specific individual where the identifiers have been removed to prevent identification of that individual.

 ²Pseudonymised Data – Data relating to a specific individual where the identifiers have been replaced by artificial identifiers to prevent identification of the individual.

 ³Mosaic Effect – The process of combining anonymized data with auxiliary data in order to reconstruct identifiers linking data to the individual it relates to.

SMART CITY needs SMART DATA needs SMART GOVERNMENT

The most significant outcome of a smart city (and the key indicator) is to provide citizens of the city alternatives and opportunities to lead a better life. This could be in the form of efficient and effective public transportation, proactive traffic monitoring and easing, automated monitoring of utility services, weather management, emergency management, public safety and more importantly an amalgam of these services through correlations. Each of these Smart City services (and please note that the above list is not exhaustive) is data-intensive and results in reams and reams of real-time data, that when leveraged can generate meaningful insights, further driving an enhanced experience for all city stakeholders.

While City agencies and governments worldwide have been spending effort through various initiatives (Ex: Share-PSI) to tap into this data and generate value, they are also limited by the resources (time, money, labor) at their disposal. What if the reams of data generated through the city/government initiatives are made available to private entities and general public, at large. Of course, this needs a careful scrutiny of what data can be shared beyond the boundaries/firewalls of the agencies. However, that should be a small hurdle to overcome considering the immense potential of the data that will be tapped into by these external stakeholders further enhancing the city ecosystem. This needs governments to open up – open up between themselves and open up to external world. This needs Open Government Data.

In an earlier blog, I had highlighted how Government data can be used in different contexts – Government to Government (G2G), Government to Business (G2B) and Government to Citizen (G2C). The progression to Open Government Data needs a methodical approach and ideally takes the following transition path. Each government agency needs to scrutinize its data to identify datasets that is sought by other agencies and identifying non-sensitive datasets that can be opened up between each other. A further level of scrutiny is required to identify the subset of data that can be exposed to non-government city stakeholders (private entities, general public).

However, not all data that can potentially be opened up will be really helpful. Some of the data may be in a very crude form and will not help the data consumers since they cannot leverage this without extensive effort and investment. For example, scanned (anonymized) application forms are of little value until the data is actually digitized through some OCR mechanism or manually. This discourages the consumer (more specifically, the technical community) to tap into the data even if it is made available. During this era of devops and agile, the idea with Open data is to provision datasets that can be easily tapped into and generate value quickly and with ease. So, how does one identify high value data sets – data that is smart by default?

What does Smart Data mean?

While there cannot be a binary method of identifying Smart data, some very detailed parameters have evolved from the discussions at The Open Group. One such discussion has arrived at the following 9 dimensions of quality that should be applied to data:While these 9 quality parameters are important, one needs to look into the specific business requirement and the corresponding datasets to assign weightage factors to each of these parameters suiting the context. It is also to be noted that each parameter will have further level of detail that has to be studied before declaring it be of high quality. For example, is Credibility defined only by the trustworthiness of sources – what if the data has undergone some transformation in the interim before being made available?

Another example – the Processability parameter mentioned above can also be studied further using the 5-star-data definition provided by Tim Berners-Lee. Most government agencies will have a mix of these different segments of rated data with a heavy leaning towards one-star and two-star data. While one-star and two-star data is fairly easy to generate, this limits data usage on the consumers’ side, when exposed and made available as Open Data. Generally, there are very few consumers willing to invest and/or competent enough to refine the provider data further to make it more consumable. And hence, the uptake of this kind of data will be low. Provider agencies will need to invest in progressing further on the maturity roadmap – make data non-proprietary, add semantics and link to related data/content. More importantly, they should adopt these new methods for all data generated till date and in the future. As a data provider agency progresses on this maturity roadmap, it will start seeing a corresponding adoption and value-generation from the larger city ecosystem. It is to be noted that the progression towards 5-star data will involve a change in organization practices and culture but once that becomes business-as-usual, the effort required is fairly low compared to the uptake one gets to see on the consumer-end.

How can governments be smart?

Most governments worldwide have opened up to the idea of Open data and the ones who have not will only delay but eventually get there. The question is no longer whether government agencies will open their data, it is when and how will they open their data. It requires strategic planning by the governments to execute initiatives of this nature and drive collaborative execution of the same across agencies. Substantial focus on adoption enablement to ensure governance and adherence to standards is essential.

Exchanging data between agencies does not come naturally to most government organizations and when they do share data, they rely on very manual or archaic methods – paper-based, phone requests, email requests etc. Initially, the agencies have to move to an operating model where data is made available on a data exchange platform through a single window (Ex: a portal). Data can be requested and procured through the same window – either in real-time or in batch mode depending on the nature of the request. At minimum, this will ease government operations and make them more effective and efficient. Also, it makes life easy for the citizen so that he/she does not have to share the same data multiple times with different agencies.

This is best implemented by encapsulating the data sharing services as APIs since it can potentially foster further innovation within the government ecosystem.

Once the data has been opened up between agencies, it makes it relatively easy to progress to share the non-sensitive data with non-government stakeholders. The API-approach can be leveraged further to encourage innovation in the digital economy.The next level of progression will be to linked open government data (LOGD) and use this as a revenue stream. LOGD can demonstrate value in a wide range of use cases that were not thought of earlier. As an example, imagine the impact of accessing real-time public transport services data (from the Transportation department) to an event in the city (organized by Tourism department) that links up with the weather data (gathered from Meteorological department) and helps the citizen plan their journey.

Governments need to take up planned initiatives to tap into the potential of locked up data. The data needs to be pruned and polished to make it more relevant and ease consumption. This data, once tapped into by the city ecosystem, can be applied in daily-life scenarios that impact the community and thereby, deliver a signature city experience. The possibilities are immense. All that is required is to take the initiative and tap into the value of the new natural resource – data. The sooner the better.

Closing thought – Is the Open Government Data story complete once government entities have made data available in 5-star format (the best possible format)? Or would you say the story has only started on a strong footing? There is a lot more to follow…

Tapping into Social, Economic value of Government Data

Data has been dubbed as the new natural resource and the possibilities it creates are numerous. Its economic value is being tapped into by private enterprises worldwide. They are leveraging data from various sources to bolster their bottom-line through advanced analytics and generating customer insights. On the contrary, governments have been very late to jump on the bandwagon because of the closed environments in which they operate and the opinion that “all” government data is sensitive. While it is known that Governments often have a lot of personal data, a closer look at the public data in the context of relevant use cases will help identify data that can potentially be opened up.

There are a range of different arguments for open government data. It could be used to facilitate government transparency, drive accountability and public participation, support technological innovation and economic growth. The possibilities are immense and the society at large can benefit from making public data available to various stakeholders. Here are a few scenarios:

Government to Government (G2G) – It is imperative that government agencies have to communicate to each other during the course of their operations. This, at most times, involves exchange of information between agencies that is contextually relevant. Traditionally, this has happened through physical paper, phone conversations or emails, at best. For example, the Ministry of Labor (MOL) will need a regular feed of the commercial permits issued within a jurisdictional area by the Ministry of Urban Planning (MUP) and commercial registrations approved by Ministry of Commerce (MOC) to check and ensure regulatory compliance to labor laws by all commercial entities. The time spent by the government agencies in fulfilling these requests is substantial considering the repetitive nature of the requests. This is an ideal scenario to identify such datasets and make them available on a Government Data Exchange (GDX). Each agency exposes the datasets from its in-house databases and makes them available as web services on the GDX. The GDX can be accessed through a portal user interface by any agency to receive latest data that is relevant to their context from other agencies. This will potentially result in operational efficiencies and better utilization of the limited government resources.

The progression to Open Data needs a methodical approach and each government agency needs to scrutinize its data to identify datasets that is sought by other agencies and identifying non-sensitive datasets that can be opened up between each other.

Government to Business (G2B) – The inherent potential of data is only limited by the number of use cases that can be defined. Governments are being forced to “do more with less” in in a challenging economic environment worldwide. With constrained resources, the governments can deliver a limited set of services, thereby cap the potential of Government data. This is where the evolution to the next phase of Open Data initiatives kicks in. A further level of scrutiny of Government datasets is required to identify the subset of data that can be exposed to non-government city stakeholders (private entities, general public).

In today’s world, having a strong API strategy isn’t just good software practice; it’s a powerful business practice. The volumes of data provided through government systems can be leveraged through APIs by various business organizations that will benefit from the information to run their operations. This will be facilitated through exposed APIs that can be consumed by the individual organizations and drive their business-specific use cases by leveraging the data from various government agencies. This doesn’t just create value for business establishments. The government wins as well by expanding the ecosystem, increasing retention, and driving up the value of the data platform. As an example – The student transportation industry depends heavily on real-time traffic conditions to ensure that the students are transported from their homes to schools and back. They can combine and correlate the traffic data, weather data, and planned events data from the various government agencies to plan/adjust their routes. Another example is the 3PL providers who can also leverage the same datasets to deliver their supply chain management functions.

Governments can potentially develop models where they can enrich datasets and make them readily consumable by business entities. Such high quality datasets can potentially be used to generate revenue on an ongoing basis by selling them for a nominal fee to business establishments while the raw datasets are still made available without any fee.

Government to Citizen (G2C) – The digital movement has infused a plethora of rich mobile apps into the citizen’s lifestyle. From finding an ideal road route based on real-time traffic to pay your utility bills – mobile has had a significant impact on our lives and enhanced our living experience. Citizens interact with multiple government agencies as part of their routine and are best equipped to identify challenges that they face during these interactions. Some of them also have potential solutions to these challenges, that when implemented to have a widespread impact on the society. They are however constrained by the limited access to government data. As was done in the case of G2B, government agencies can potentially make data available to the Citizens. This is when the social value of data could potentially be tapped into by the citizens themselves. As an example – Mandi Trades is a Location based F2S (Farm to Shop) Trading Platform for agricultural products. The App provides the daily agricultural commodity prices as updated by Open Government Data Platform in India.

There are many such citizen-centric applications of open data in the emerging markets, developed by the citizens themselves. This drives engagement of citizens and more importantly, it drives social uplift.

Indeed governments need to approach their open data strategies with an open mind. Governments need to take up planned initiatives to tap into the potential of locked up data. The data needs to be pruned and polished to make it more relevant and ease consumption. The potential that Open data holds is immense – no two ways about it.

The “Smart” in Smart Cities

Having traveled to different countries, I am quite demanding when it comes to my city experience.  I am sure that today’s “well-traveled” urban resident also has equally high (if not higher) expectations from their city. The overall city experience is driven by the city planner’s vision for their city and execution of this vision by various city agencies. In today’s scenario – this vision, more often than not, involves an aspiration to transform into a Smart City. I am penning this blog against the backdrop of a huge awareness for Smart City initiatives in the emerging markets – MEA (Middle-East Africa) and India.

I work in the MEA region that brings together a spectrum of countries that are at different points in their evolution journey and are driving Smart City programs in pockets. I come from India and there has been a recent announcement by the government about developing 100 Smart Cities in 5 years. An obvious observation would be that a resident from Dubai (UAE) has very different expectations from one in Nairobi (Kenya) and a resident in Johannesburg (South Africa) has different expectations from the one in Bangalore (India). However, every city dweller wants one thing in common – a better way of life in the cities that they reside. Everyone likes to be at a place that welcomes him/her and delivers a signature city experience.

So, what makes a city “Smart”?

The City ecosystem is made up of important entities – people, agencies, systems, procedures et al. Smart City initiatives have to be tied to these entities and drive improvements and deliver exceptional experiences. I believe the transformation into a Smarter City has to go through a progression path spread over three waves.

Wave 1 – Foundational Smart City Initiatives

City planners would have a wide range of possible initiatives that they can consider to make their city “Smart”. While taking them up at one go could be overwhelming – not just for the planner but also for the average resident – there are services that the resident expects “bare-minimum” from a Smart City. It is prudent that cities evolve by establishing a strong foundation that can be leveraged and extended further with time. Here is a sample list of these Foundational Smart City initiatives:

Wave 2 – Advanced Smart City Initiatives

With the number of Smart City programs being executed worldwide, there will always be a demand on city planners to ensure that their city stands out from the crowd. Of course, this can only be done once the foundational setup is in place. A unique experience for the Smart city resident is essential to ensure stickiness and brand appeal. These initiatives build on top of the foundational initiatives and further differentiate the “city experience” 

Wave 3 – Correlation between Initiatives

Having established the Smart City initiatives, a mature Smart city will have to deliver an “one-city” experience to its residents across all interfaces with the residents. This can be achieved by having the data between different initiatives integrated into one data hub and generate correlations between various sets of silo-ed data. An interesting example would be to correlate weather data with water consumption levels to draw patterns on a hot day vs cloudy day scenario and leverage this further to predict water usage in the future. Another example would be adapting traffic management based on incidents happening in the water network (sewage pipe leaks). A representation of this solution is shown here.

What makes a city “Smart” is dependent on where you are on the evolution journey. For established cities that want to evolve into Smart Cities, there can never be a standardized journey template since each city will have its unique needs, demands and constraints. For Greenfield cities, like the ones coming up in emerging markets (Dubai Design District, Palava, Lavasa et al), they have an advantage of not being bound by existing systems/infrastructure. They can be innovative and plan their journey so that they can extend and scale over time with an end-objective of delivering a differentiated city experience to their residents.