Making the world a better place, one analysis at a time

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1. Big Data,PublicSector, andCrowdSourcingPossibilitiesUnlimited?Manish Arora, SuasiveConsulting & Analytics 2. 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 theintersection of the three which offers unique and immense possibilities that can truly make theworld a better place.Before we get into discussing what is so special about the overlap of the three, let us go throughsome of the key characteristics of each:Copyright 2014, Suasive Consulting & Analytics. All rights reserved.Big Data: Typically characterised by 3 Vs: Volume, Velocity, and Variety. Major corporations are working to leverage opportunities created by Big Data and have hadvarying degrees of success with their Big Data initiatives. Small and Medium Enterprises have been successful only in pockets, primarily owing to theirinability to sustain the technological footprint or skills required. I should also add that due totheir limited scale, SMEs also dont always have a solid business case for making Big Datainvestments. Governments, despite being data rich, have often been careful in how they leverage Big Datasince they dont 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 disintermediationcaused 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. Forexample, the screenshot below is from, a site maintained by Ministry ofCommunications and IT, Government of India.Public Sector: Public sector enterprises find themselves under pressure to reduce costs and deliver greaterbang for buck. 3. Across many countries, governments seem to be suffering from trust deficit, particularlyafter 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 adoptionof technology, and need to prove their raison dtre through the results that they generate.So what is interesting about the intersection of the Big Data, Crowdsourcingand Public Sector?The possibility of raising the efficiency and effectiveness of public sector enterprises, by leveragingBig Data, through crowdsourcing manpower and skills [primarily] and infrastructure [possibly] is aconcept 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 atheoretical level why it seems like a good idea: Using Big Data to drive decision making in a very transparent and accessible manner willallow governments to win trust. Crowdsourcing also allays the concerns aroundinappropriate use of data, since no malevolent objectives can be served throughcrowdsourcing [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 improvetheir 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 therespective governments, even in mature democracies, it will create a sense of belonging forpeople and make them feel a part of the governance process. There is a direct cost saving associated with crowd sourcing as compared to more traditionalmethods of sourcing. This will directly lead to greater value creation by the public sectorenterprises. 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 thegovernments.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 countrieswhere issues due to corruption are relatively more common. Having said that, it is easy to see howsomething similar could be employed in a different set up to the same effect. Also, while this is anexample of public-sector-leading analytics, the same could very well be public-sector-leddepending upon the political will of a particular administration.Copyright 2014, Suasive Consulting & Analytics. All rights reserved. 4. Intersection of Big Data, Public Sector and Crowdsourcing A PossibleApplicationIn India it is fairly common for roads to have potholes. Potholes can be seen throughout the year butthe 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 everyyear in accidents directly related to pothole menace.Copyright 2014, Suasive Consulting & Analytics. All rights reserved. 5. 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 inthe mix) that can only withstand the pressure of the traffic until the next time it rains and the sandgets 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 andbureaucrats who influence the process of contractor selection. Political parties in power blame theparties who came to power before them and bureaucrats blame the politicians and it is an endlessCopyright 2014, Suasive Consulting & Analytics. All rights reserved. 6. blame game. In the end, a common man can never successfully hold anyone accountable for thecondition of the roads.So what can be done?Imagine that anytime someone saw a pothole, he/she takes a picture with geo-tagging on anduploads it to a particular website. This will ensure that the picture properties will contain latitudeand longitude information as shown in the example below:A simple program can be written to access geo-tagging information for each picture, while humanintelligence required to tag the condition of the road can be crowdsourced. This analysis whendone, will lead to a table of information such as below:Latitude Longitude Condition of road13.05 77.5 Extremely PoorCopyright 2014, Suasive Consulting & Analytics. All rights reserved. 7. It is also possible to get the data about the political party in power and the contractor1 responsiblefor road building/repair for a particular Latitude and Longitude from public records. Again, the taskcan be crowdsourced. Once this data is available then it will lead to a table such as below:Latitude Longitude Condition of road Political Party Contractor13.05 77.5 Extremely Poor XYZ ABCImagine, the table above with hundreds of thousands of records covering pretty much all the roadsin the city. It is easy to see the power of making such a data-store available publicly. Isnt it?One can draw all kinds of insights from it. For example, is there a correlation between a certainpolitical party and a certain contractor winning the bid, is there a correlation between condition ofthe roads and the political party in power, or is there a correlation between the condition of theroads and a certain contractor in-charge of building or repairing? The analysis can then be used byjournalists 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 orMedia can then ask, Why do the potholes reappear, and why isnt the contractor able to fix them forgood? 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 rightdirection. To the extent that corruption feeds on information asymmetry, every time there issomething that reduces the information asymmetry, it indirectly helps reduce avenues as well asupside of corruption.In ConclusionThe ability of Big Data to provide hitherto unavailable and truly meaningful insights is real. Thepublic sector has a lot of work to do in order to improve its effectiveness, particularly in the case ofdeveloping counties that are often crippled by mass corruption. And so, the public sector has muchto benefit from Big Data. Crowdsourcing is a viable, and arguably the preferred, option for publicsector 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 thechallenges facing the public sector enterprises in most economies?Please do share your thoughts, comments and feedback with me. I can be reached In some cases, the details of the contractor responsible may not be available due to maintenance of poorrecords 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. 8. References and Images: 2014, Suasive Consulting & Analytics. All rights reserved. 9. About the author:Manish has been a keen observer of the Indian outsourcing industry for more than a decade and setup Suasive Consulting & Analytics, a Bangalore based analytics service provider, to blend the bestpractices learnt from working with large international businesses and observing the home-grownservice provider industry.Prior to starting his own business, Manish worked as a Principal Consultant with a niche consultingcompany (ISG), where he advised his clients on their sourcing strategies.Prior to ISG, Manish worked at British Telecom (BT), London as Business Analysis & Planning Directorfor BT Innovate & Design, where his mandate was to leverage the in-house Business Intelligencecapabilities to reduce the operating costs.Manish started his career in 2001 with Amdocs, where he assisted leading global companies on theirstrategic transformation programmes.Manish holds an MBA from INSEAD (France) and Bachelor of Engineering (Honours) in ComputerScience from Punjab Engineering College, Chandigarh. He lived and worked in EU and UK from 2001till 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 Suasive Consulting & Analytics:Suasive Consulting & Analytics is a Bangalore (India) based analytics service provider that helpsclients worldwide address their business problems through data-driven decision making andleveraging various data assets spread across the organization. We serve a host of industries and areable 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 2014, Suasive Consulting & Analytics. All rights reserved.