Roel Castelein (Global) - The Big Data Fairy Tale
Master Data Management

Roel Castelein (Global) - The Big Data Fairy Tale

Fairy tales usually start with ‘Once upon a time ...' and end with ‘... And they lived long and happily ever after'. But nobody explains ‘how' the heroes live long and happily ever after. Big data (analytics) promise to transform your business, but just as in fairy tale endings, big data will not explain ‘how' to transform your organization. In my view, big data might spark some behavioral change or open people's minds, but it will not transform organizations. At best, big data evolves organizations. Let's look at the concept and a concrete example to draw conclusions.

What big data analytics does is take a bunch of data, analyze and visualize it, and then derive insights that potentially can improve your organization or business. Based on these insights the actual transformation can begin, but it requires more than just big data. Let's have a look at a classic example of data analytics; the reduction of crime in New York under Mayor Giuliani with the help of CompStat.

CompStat is a data system that maps crime geographically and in terms of emerging criminal patterns, as well as charting officer performance by quantifying criminal apprehensions. The key to success was not the data or analysis, but that the organizational management that used the data and analysis was effective. Processes, structures and accountability were setup to drive the transformation. In weekly meetings, NYPD executives met with local precinct commanders from the five boroughs in New York to discuss the problems. They devised strategies and tactics to solve problems, reduce crime, and ultimately improve quality of life in their assigned area. CompStat tracked the results of these strategies and tactics, and whether they were successful or not. Precinct commanders were held accountable for the results.

Drawing upon my own experience, I know how difficult an organizational transformation is. Even if you have the data and the analysis that shows things need to change, it requires much more than data analysis. Let's assume that the data uncovers opportunities for improvement, either in reducing cost or in increasing revenue. The next step is to design the changes in processes, in people's roles, in org charts and in the systems. This usually entails a two pronged approach; communicate the change in org charts, processes and roles, and engrain these changes in the systems to track the change results. This tracking creates a feedback loop, necessary to manage the transformation.

Another challenge in the big data transformation message is finding the right people. Ideally the team leading the transformation needs to understand an organization's data, enriched with outside data, then know how to do data analysis, and once the results are there, strategically communicate the change to get everybody on board. Next, the transformation team needs to set up a tracking and feedback process that holds participants accountable for the transformation results. And when participants do not play along, have an escalation process in place, with the possibility for punitive measures.

In the same way that Giuliani fired one of the precinct commanders when he showed up drunk at the first CompStat meeting, big data systems require a complementary management philosophy to ensure whatever transformational insights are derived get implemented and controlled.

So, when the advertisements claim that big data will transform your business, remember that big data brings the potential for transformation, not the actual transformation. That still requires commitment and hard work, just like ‘living long and happily ever after'. That's why they are called fairy tales.

By Roel Castelein, GTM Strategy for EMEA, EMC

 

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Comments

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Udayan Banerjee on September 28 2012

Is it not a fallacy to assume that when there is lots of data there must be some useful actionable hidden meaning / trend inside it? http://setandbma.wordpress.com/2012/02/02/big-data/

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Theodore Omtzigt on September 29 2012

For a subset of the market, your analysis is spot on. For enterprises and governments that are trying to leverage deep analytics to improve their operational performance, the continuous improvement feedback loop (and a mechanism to kill the loop once incremental performance is showing diminishing returns) is key. However, you are missing the biggest opportunity that big data is opening up in the market and that is new products, services, and business models. The analytics are fully integrated into the product or service as the key differentiator. Recommenders are the obvious example, but embedded intelligence and sensor fusion will enable new products that couldn't be realized without big data/deep analytics techniques. No change in culture required: it is the nature of the product.

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Rubberman on September 30 2012

Big data (Hadoop) plus analytics are not a panacea, and are not magic. However, they are TOOLS that can help any organization make sense out of masses of data that are not amenable to normal data storage and analytical means. Six months ago, I and a colleague who understood this, had to pull hair to get resources in order to prove this. Now, management is no longer wondering if this is worth our time, but asking (loudly) when we will be in production! We started with 2 of us and a vision. We are now a multi-national team with 3-4 PhD mathematicians and others devising analytical tools to help our company improve customer experience, and maximize financial return on our investment in internet presence.

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Eirik Rossen on October 01 2012

Castelein's remarks are pertinent. For the sake of credibility I advise correcting the sentence about the "eight" boroughs in New York City.

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Dave Thompson on October 01 2012

Big Data seems a perfect fit for Gartner's Hype Cycle. Currently, the industry is experiencing Inflated Expectations, we should expect some Disillusionment then Enlightment before plateuing out to Reality, where Big Data becomes another important tool in our productivity kit, as Rubberman suggests. One assumption of particular concern is that we will be able to gather bunches of big data, analyze it, and suddenly understand how our businesses should reorganize. There are many factors, some of which are not amenable to big data tools, that affect business efficiencies. Big data analytics can certainly help in some instances, but it isn't the final answer, or, often, isn't even the most important factor.

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Vish Ramdas on November 29 2012

I agree with Theodore Omtzig that whats being missed out is the new models that emerge in service, business and producs.. What Big-Data wont transform is monopolistic services like government that needs a larger change mechanism, it also wont change legacy lare orgs that easily.. i agree with the author on that.. but what it would do is transform industries from the inside out and there by disrupt incumbents.. what stops a new org coming up with new models using data insights? and not having the incumbency of large un-moving people parts? thats my question while there will be a hype cycle, that hype is created by our perceptions and mis-conceptions of what big-data can do and the selling that goes on with it.. but there will be a silent under current of transformation in garages and else where were industries will get shifted..

no-images

Udayan Banerjee on September 28 2012

Is it not a fallacy to assume that when there is lots of data there must be some useful actionable hidden meaning / trend inside it? http://setandbma.wordpress.com/2012/02/02/big-data/

no-images

Theodore Omtzigt on September 29 2012

For a subset of the market, your analysis is spot on. For enterprises and governments that are trying to leverage deep analytics to improve their operational performance, the continuous improvement feedback loop (and a mechanism to kill the loop once incremental performance is showing diminishing returns) is key. However, you are missing the biggest opportunity that big data is opening up in the market and that is new products, services, and business models. The analytics are fully integrated into the product or service as the key differentiator. Recommenders are the obvious example, but embedded intelligence and sensor fusion will enable new products that couldn't be realized without big data/deep analytics techniques. No change in culture required: it is the nature of the product.

no-images

Rubberman on September 30 2012

Big data (Hadoop) plus analytics are not a panacea, and are not magic. However, they are TOOLS that can help any organization make sense out of masses of data that are not amenable to normal data storage and analytical means. Six months ago, I and a colleague who understood this, had to pull hair to get resources in order to prove this. Now, management is no longer wondering if this is worth our time, but asking (loudly) when we will be in production! We started with 2 of us and a vision. We are now a multi-national team with 3-4 PhD mathematicians and others devising analytical tools to help our company improve customer experience, and maximize financial return on our investment in internet presence.

no-images

Eirik Rossen on October 01 2012

Castelein's remarks are pertinent. For the sake of credibility I advise correcting the sentence about the "eight" boroughs in New York City.

no-images

Dave Thompson on October 01 2012

Big Data seems a perfect fit for Gartner's Hype Cycle. Currently, the industry is experiencing Inflated Expectations, we should expect some Disillusionment then Enlightment before plateuing out to Reality, where Big Data becomes another important tool in our productivity kit, as Rubberman suggests. One assumption of particular concern is that we will be able to gather bunches of big data, analyze it, and suddenly understand how our businesses should reorganize. There are many factors, some of which are not amenable to big data tools, that affect business efficiencies. Big data analytics can certainly help in some instances, but it isn't the final answer, or, often, isn't even the most important factor.

no-images

Vish Ramdas on November 29 2012

I agree with Theodore Omtzig that whats being missed out is the new models that emerge in service, business and producs.. What Big-Data wont transform is monopolistic services like government that needs a larger change mechanism, it also wont change legacy lare orgs that easily.. i agree with the author on that.. but what it would do is transform industries from the inside out and there by disrupt incumbents.. what stops a new org coming up with new models using data insights? and not having the incumbency of large un-moving people parts? thats my question while there will be a hype cycle, that hype is created by our perceptions and mis-conceptions of what big-data can do and the selling that goes on with it.. but there will be a silent under current of transformation in garages and else where were industries will get shifted..

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