Story of 5 Blind Men and an Elephant and your Big Data Strategy

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Driving value from existing data is one of the most common challenges faced by organizations, however, that doesn’t mean that you should not be working towards a Big Data Strategy. You might think you want to implement a big data strategy but feel you should utilize the data you already have first. This dilemma (or confusion) leads to not having a comprehensive strategy for leveraging your current data (Big, Small, Fast, and Slow) but to plug holes in your current data landscape with the addition of a few new tools and technologies. You have to take this seriously – it’s a once in a lifetime opportunity for you to enable a holistic business transformation in your organization. In general, your Big Data Strategy is not about getting away from your current investments in data technology and replace it with something new. It’s about having a well-rounded strategy – to enhance and equip you for the next several years.

Big Data analytics done right will always tell the truth (facts & insights), but you may still be concerned about the outcome. Like it or not the fact is that many data analysts make assumptions based on their own perceptions or the guidance given by their leadership resulting in the unintentional skewing of the resulting data analysis. These results could lead to missed opportunities to cut cost, increase revenue, or both. As you drive towards a Data Driven culture, transparency is the goal you should be striving to achieve. It may take time to change this mindset, but it is important to start change here.

Building a Big Data technology solution is relatively easy. The challenge is the evolutionary change required to become a data-driven culture—ensuring data is part of your day to day decision making—is extraordinarily difficult. As with any cultural change, you must manage your organization’s emersion into a data-driven culture with patience, purpose and meaning. That is, marrying your organizational temperament with your strategic imperatives, goals, and objectives. This is easier said than done. It reminds me of the story about the blind men and an elephant (the full story covered below).  The symbolism in the story may represent your organization.

I have heard people discussing their 200 node Hadoop clusters and taking pride in their accomplishments while the business is still asking “how do I benefiting or derive value from it?”. Another group (may be IT) tries to put their arms around the Big Data strategy by controlling the governance process as their primary focus area whereas the business may be focused on self-service (which could be inhibited by the governance process). The majority will be looking at how to consume the information – the end consumers of the data and a small contingent will need to go deeper into the data lake and come up with some new insights – for Innovation, Growth or even Operational Improvements.

Here is the complete version of the story “The Blind Men and The Elephant” as I have read in an article recently.

“Once an elephant came to a small town. Five blind men also lived in that town, and consequently, they also heard about the elephant but had never seen an elephant before, and were eager. As they are blind, they decided to go and feel the elephant with hands. They could then get an idea of what an elephant looked like. They went to the town where all the people made room for them to touch the elephant. Later on, they sat down and began discussing their experiences.  One blind man, who had touched the trunk of the elephant, said that the elephant must be like a thick tree branch.  Another who touched the tail said the elephant probably looked like a snake or rope.  The third man, who touched the leg, said the shape of the elephant must be like a pillar.  The fourth man, who touched the ear, said that the elephant must be like a huge fan; while the fifth, who touched the side, said it must be like a wall. They sat for hours and argued, each one was sure that his view was correct.  Obviously, they were all correct from their own point of view, but no one was quite willing to listen to the others.  Finally, they decided to go to the wise man of the village and ask him who was correct.  The wise man said, “Each one of you is correct, and each one of you is wrong.   Because each one of you had only touched a part of the elephant’s body.  Thus you only have a partial view of the animal.  If you put your partial views together, you will get an idea of what an elephant looks like.”

Do you see these blind men in your organization? Do you have these types of arguments? Who is going to be the wise man in your Organization?

I would love to hear your thoughts.

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5 Comments
  1. Great article to explain complex organizational challanges.

    • Thanks Rushikesh. Good to hear that it is resonating.

  2. I really enjoyed your article Rajeev. The irony is, as we speak things are even changing towards Saas, PaaS and more importantly IaaS. Hadoop /HDFS is already in the past, with the spark coming in to the mix. So the open source is a challenge to adopt and to derive value out of data and to implement the whole 9 yards of Bigdata organizations has to have some dynamic people who are ready to adapt and culture to innovate.

    • Thanks Vasu for taking time to read the article and provide your inputs. I agree with your sentiments that things are changing and in such a pace! I believe its time for most of the enterprises to take a holistic look at their Data/Information landscape and come up with a long term strategy that is aligned to their business priorities. They should not continue the model of ‘accumulating’ any new technologies that just increases the complexity and of course the cost with minimal to no value to the business. It is the time and opportunity for a re-engineering exercise – a very carefully crafted plan by augmenting the existing investments with the new technologies.

  3. That’s indeed a good article, Rajeev. Keep writing and inspiring those who are interested in Big Data analytics which I think, is quite awesome! Thanks, Ajith

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