Disruptive Innovation - A new era of Crowdsourced Data Analytics

Published by MBA Skool Team, Published on November 26, 2011

On November 3,2011 news came out that Kaggle has bagged $11 million through VC funding. The money came from Silicon valley VCs Khosla Ventures, Index Ventures,SV ventures and others including Paypal. Kaggle entered the business of solving complex data analytics problems through contests in April, 2010. Since then it has successfully hosted umpteen contests and boasts of having almost 17000 data scientists across the globe. The point that stands out here is that there is a real substance in crowdsourced data analytics model. More so, when companies are grappling to manage “Big Data” which has exponentially increased in last five years; Kaggle’s success in garnering covetedVC funding is a testimony to this judgement. Let’s analyse the aforementioned model and its impact on the market.


A brief overview of the model

The below business model explained subsequently is that used by crowdANALYTIX which is yet another revolutionary product in the crowdsourced data analytics space.

The CA model (read crowdANALYTIX) encompasses two key aspects: data management and data analytics. CA model talks about helping clients to make protect their Big Data repository by porting it to more trusted integration platforms like Hadoop and Mahout. Post data integration, data analytics will be done on a Revolution Analytics platform, which has strategic partnership with crowdANALYTIX. The data analytics process is seamlessly structured in the following manner:

A client details out their requirements to CA to begin with. CA has partnerships with lead analysts, 90% of whom have advanced degrees in statistics. These lead analysts break the problem into subparts and each subpart will inturn be a contest on CA platform. Crowd will solve the problems and submit solutions. The whole process will be administered by lead analysts. When solutions of all the subpart problems are obtained, lead analyst will aggregate the solution in a meaningful manner and submit it to the client.

The process adds a significant value over existing process of data analytics through consulting enterprises in:

  • 20-30% cheaper than existing alternatives
  • Access to large base of global professionals and talents
  • Quicker delivery of solutions

Impact Assessment

The business model has immense capability to bring about a paradigm shift in the way data is managed, analysed and optimized in large and small enterprises. Below are a few impacts listed:

I. Analytics, now a reality for SMEs

Analytics till today is understood as a luxury of the cash rich companies. SMEs generally abstain from such lavish expenditures and hence they always had to rely on their own intuitive decision making. They still don’t have any robust mechanism to verify their assumptions because tools like market research and data analytics is not for them, they believe. Not anymore! Companies like Kaggle and Crowdanalytix provides them with such non-expensive and reliable platform for analytics that SMEs can now espouse structured decision making in free will.

II. Analytics market: Now an open field

The issue that small analytics consultants face today is that they are overshadowed by large consulting organizations. Small consultants include both individual consultants and small boutique consultants. These small consultants have to fight a stiff battle for every single project. Even if they win one, their margins are eaten up by their overboard sales efforts to grab one assignment. Hence, smaller consultants remain low on cash. The new crowdsouring model brings them a sigh of relief. Today, they don’t have to bid for projects; they are up on the web. The consultant wins money not because of the size of his organization but solely on his competency. Second way these consultants earn bucks is by joining network of lead analysts as mentioned previously in the article.

Hence, the new business model has opened the field and for the first time grass is not greener on the other side!

III. Coupling of data management and data analytics

As explained earlier, the new crowdanalytix model will not only help companies solve their critical analytics problems, but also help clients port their big data onto platforms like Hadoop, Mahout etc. This signifies that CA(Crowdanalytix) promises to be a complete data management and analytics service provider for enterprises. Do companies need more to cheer about! Especially in the times when enterprises are bombarded with data, petabytes of data, relational data, non-relational data, data which make them go nuts.

Just to put things into perspective, this is an essence of a petabyte of data:

Source: www.techwhizz.com/visualizing-petabyte-age-inforgraph/

More so, companies are having a hard time to locate the “Big Data” experts, who inturn are having a roll of the lifetime. The new business model will increase accessibility of companies to right experts.

Thus crowdsouring model of analytics and data management is an out and out winner.

IV. Decision lag will reduce

In the fiercely competitive market, companies need to make decisions all the time. Decisions regarding product development, sales promotion success, marketing planning, operational efficiency so on and so forth. But even today, managers rely on their own intuitive judgements to take decisions with no way to verify decisions. Why? Because the cost of verification of their decisions is very high both in terms of time and money. The model of crowdsourced data analytics will reduce the time of problem solving and the cost is significantly less than the primitive ways of analytics. Hence, as a manager I can get routine analytics stuff done without facing complexities of locating analytics companies, RFP process,Fee negotiation, Handing over the data and so on. In the new crowdsouring process all I need to do is contact one company and get the contest on the site very next day. The problem can be painfully complex to extremely simple.

Hence, managers don’t have to hesitate or panic before decision making for the lack of channel of verification of their decisions.

V. Big analytics companies and management consulting firms will employ Crowdsourced Analytics to reduce costs

An interesting observation is that existing large analytics consultants like Deloitte, HSBC, Boston Analytics, Oracle etc. will see value in crowdsourcing some of their work rather and hence will eventually trim their in-house team sizes. The process of problem solving in big analytics companies is that of breaking down large problem into subparts, finding analytical solutions to each subpart and merging the solutions together. In due course of time even such companies would see a value in transforming some of their fixed costs(of having full time analysts on board) to variable costs(of crowdsourcing some of the analytics problems). The same is true for management consulting firms like Bain and Co., Accenture, Booz Allen etc.

It would be apt to say that crowdsourced analytics is not exactly a competitor for large analytics firms, rather it is an efficient tool which fits into their current processes.

After cloud computing, a business model that can boast of disrupting an existing process is that of analytics through crowdsouring. However, both the companies, i.eKaggle and crowdANALYTIX are new to the market. The success of the model is yet to be tested. The quality of solutions obtained through this model is yet to be verified. Secondly, a certain matrix has to be devised to measure the success of the crowdsoured data analytics model. Parameters like quality, clarity of recommendations, lead/lag time of delivery should be given relevant weightages.

In the present times of weak global economy, crowdsourced data analytics is nothing less than a smooth breeze for businesses.

This article has been authored by Ayush Malhotra from NMIMS

Views expressed in the article are personal. The articles are for educational & academic purpose only, and have been uploaded by the MBA Skool Team.

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