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Big Data, Public Sector, and Crowd Sourcing
Possibilities Unlimited?
Manish Arora, Suasive Consulting & Analytics
Copyright © 2014, Suasive Consulting & Analytics. All rights reserved.
Big Data, Crowdsourcing, and Public Sector – Possibilities Unlimited?
In this paper, I want to talk about three distinct areas: Big Data, Crowdsourcing, and Public Sector.
Each of the these areas merits a paper on its own but through this paper I want to argue that it is the
intersection of the three which offers unique and immense possibilities that can truly make the
world a better place.
Before we get into discussing what is so special about the overlap of the three, let us go through
some of the key characteristics of each:
Big Data: Typically characterised by 3 Vs: Volume, Velocity, and Variety.
Major corporations are working to leverage opportunities created by Big Data and have had
varying degrees of success with their Big Data initiatives.
Small and Medium Enterprises have been successful only in pockets, primarily owing to their
inability to sustain the technological footprint or skills required. I should also add that due to
their limited scale, SMEs also don’t always have a solid business case for making Big Data
investments.
Governments, despite being data rich, have often been careful in how they leverage Big Data
since they don’t want to be seen as acting in a “Big Brother” fashion.
Crowdsourcing: Has been around for some time and is essentially a by-product of “disintermediation”
caused by the internet.
Used by organizations of all sizes, big and small, for a variety of tasks.
Crowdsourcing has also been employed by some governments in very innovative ways. For
example, the screenshot below is from www.mygov.in, a site maintained by Ministry of
Communications and IT, Government of India.
Public Sector: Public sector enterprises find themselves under pressure to reduce costs and deliver greater
bang for buck.
Copyright © 2014, Suasive Consulting & Analytics. All rights reserved.
Across many countries, governments seem to be suffering from trust deficit, particularly
after having had to put public money to compensate for excessive private sector risk-taking.
Public sector enterprises need to show greater transparency in execution, agility in adoption
of technology, and need to prove their raison d’être through the results that they generate.
So what is interesting about the intersection of the Big Data, Crowdsourcing
and Public Sector?
The possibility of raising the efficiency and effectiveness of public sector enterprises, by leveraging
Big Data, through crowdsourcing manpower and skills [primarily] and infrastructure [possibly] is a
concept that can truly change the world for better.
I would like to argue my case by giving an example but before I get to that, let us consider at a
theoretical level why it seems like a good idea:
Using Big Data to drive decision making in a very transparent and accessible manner will
allow governments to win trust. Crowdsourcing also allays the concerns around
inappropriate use of data, since no malevolent objectives can be served through
crowdsourcing [by definition].
The applications are limitless and can be public-sector-led or public-sector-leading (as in,
getting governments to act). Therein lies the ability for public sector enterprises to improve
their execution regardless of whether they are acting proactively or reactively.
At a time when there is a sense of “us versus them” between the populations and the
respective governments, even in mature democracies, it will create a sense of belonging for
people and make them feel a part of the governance process.
There is a direct cost saving associated with crowd sourcing as compared to more traditional
methods of sourcing. This will directly lead to greater value creation by the public sector
enterprises.
There are significant indirect benefits as well, such as skills building, skills identification,
generating new business ideas, and innovation, all of which are extremely valuable for the
governments.
Now, I would like to expand the argument further by giving an example application.
The case study that follows is probably easier to relate to for readers from developing countries
where issues due to corruption are relatively more common. Having said that, it is easy to see how
something similar could be employed in a different set up to the same effect. Also, while this is an
example of “public-sector-leading” analytics, the same could very well be “public-sector-led”
depending upon the political will of a particular administration.
Copyright © 2014, Suasive Consulting & Analytics. All rights reserved.
Intersection of Big Data, Public Sector and Crowdsourcing – A Possible
Application
In India it is fairly common for roads to have potholes. Potholes can be seen throughout the year but
the problem is particularly pronounced each year during and after the monsoon (tropical rains)
season. It is not uncommon for one to come across pictures such as the ones below:
In extreme cases, accidents such as the one shown below happen. Up to a dozen people to die every
year in accidents directly related to pothole menace.
Copyright © 2014, Suasive Consulting & Analytics. All rights reserved.
Why does no one repair these roads?
Well, the answer is they do. Actually, they do it more often than they do it in most other countries.
But each time they do it using substandard material (often with disproportionate amount of sand in
the mix) that can only withstand the pressure of the traffic until the next time it rains and the sand
gets washed away.
How can they get away with it?
There is a nexus between the contractors who are supposed to fix the roads and the politicians and
bureaucrats who influence the process of contractor selection. Political parties in power blame the
parties who came to power before them and bureaucrats blame the politicians and it is an endless
Copyright © 2014, Suasive Consulting & Analytics. All rights reserved.
blame game. In the end, a common man can never successfully hold anyone accountable for the
condition of the roads.
So what can be done?
Imagine that anytime someone saw a pothole, he/she takes a picture with “geo-tagging” on and
uploads it to a particular website. This will ensure that the picture properties will contain latitude
and longitude information as shown in the example below:
A simple program can be written to access geo-tagging information for each picture, while human
intelligence required to “tag” the condition of the road can be “crowdsourced”. This analysis when
done, will lead to a table of information such as below:
Latitude Longitude Condition of road
13.05 77.5 Extremely Poor
Copyright © 2014, Suasive Consulting & Analytics. All rights reserved.
It is also possible to get the data about the political party in power and the contractor1 responsible
for road building/repair for a particular Latitude and Longitude from public records. Again, the task
can be crowdsourced. Once this data is available then it will lead to a table such as below:
Latitude Longitude Condition of road Political Party Contractor
13.05 77.5 Extremely Poor XYZ ABC
Imagine, the table above with hundreds of thousands of records covering pretty much all the roads
in the city. It is easy to see the power of making such a data-store available publicly. Isn’t it?
One can draw all kinds of insights from it. For example, is there a correlation between a certain
political party and a certain contractor winning the bid, is there a correlation between condition of
the roads and the political party in power, or is there a correlation between the condition of the
roads and a certain contractor in-charge of building or repairing? The analysis can then be used by
journalists and citizens to ask all kinds of questions.
It is easy to add another dimension of timestamp (based on time when the picture was clicked)
which will allow analyses such as how often does a pothole appear in the same place? Citizens or
Media can then ask, “Why do the potholes reappear, and why isn’t the contractor able to fix them for
good?” or “Why has a particular contractor been reselected despite a poor record?”
While corruption remains a deep-rooted problem that will not go away with some magic Big-Data-
silver-bullet, every such effort that goes towards ensuring greater transparency is a step in the right
direction. To the extent that corruption feeds on information asymmetry, every time there is
something that reduces the information asymmetry, it indirectly helps reduce avenues as well as
upside of corruption.
In Conclusion
The ability of Big Data to provide hitherto unavailable and truly meaningful insights is real. The
public sector has a lot of work to do in order to improve its effectiveness, particularly in the case of
developing counties that are often crippled by mass corruption. And so, the public sector has much
to benefit from Big Data. Crowdsourcing is a viable, and arguably the preferred, option for public
sector when it comes to sourcing skills and manpower required to leverage Big Data.
What do you think about this article? And what do you think about Big Data, Crowdsourcing, and the
challenges facing the public sector enterprises in most economies?
Please do share your thoughts, comments and feedback with me. I can be reached on
1 In some cases, the details of the contractor responsible may not be available due to maintenance of poor
records by the departments concerned. The lack of information, in such cases, is a data point in itself.
Copyright © 2014, Suasive Consulting & Analytics. All rights reserved.
References and Images:
http://www.change.org/p/fix-the-potholes-in-bangalore
http://www.jhatkaa.org/bbmp-fix-the-bangalore-potholes/
http://ibnlive.in.com/news/potholed-india-makes-life-miserable-in-cities/405837-62-
129.html
http://ibnlive.in.com/news/after-garbage-menace-bangalore-residents-deal-with-
pothole-crisis/292957-62-132.html
http://blogs.ft.com/beyond-brics/2013/08/06/mumbais-potholes-going-nowhere/
http://ibnlive.in.com/news/bangalore-potholes-scam-that-swallows-rs-3000-crore-
every-year/415416-62-129.html
Copyright © 2014, Suasive Consulting & Analytics. All rights reserved.
About the author:
Manish has been a keen observer of the Indian outsourcing industry for more than a decade and set
up Suasive Consulting & Analytics, a Bangalore based analytics service provider, to blend the best
practices learnt from working with large international businesses and observing the home-grown
service provider industry.
Prior to starting his own business, Manish worked as a Principal Consultant with a niche consulting
company (ISG), where he advised his clients on their sourcing strategies.
Prior to ISG, Manish worked at British Telecom (BT), London as Business Analysis & Planning Director
for BT Innovate & Design, where his mandate was to leverage the in-house Business Intelligence
capabilities to reduce the operating costs.
Manish started his career in 2001 with Amdocs, where he assisted leading global companies on their
strategic transformation programmes.
Manish holds an MBA from INSEAD (France) and Bachelor of Engineering (Honours) in Computer
Science from Punjab Engineering College, Chandigarh. He lived and worked in EU and UK from 2001
till 2011 and has been living and working primarily in India and SE Asia since 2011.
To get in touch with Manish, please send an email to [email protected].
About Suasive Consulting & Analytics:
Suasive Consulting & Analytics is a Bangalore (India) based analytics service provider that helps
clients worldwide address their business problems through data-driven decision making and
leveraging various data assets spread across the organization. We serve a host of industries and are
able to deliver all our services in English and Spanish in an extremely cost-effective manner.
To get in touch with Suasive Consulting & Analytics, please send an email to
