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Minimum viable data

by Simon Spyer on May 14, 2013 9:21:00 AM

Big data is getting bigger.

Most would accept the potential. Fewer would know where or how to start.

There's always the temptation just to start doing som

ething - making an investment in technology, agencies or in data scientists.

But it's perhaps a little risky.

Our approach is finding the minimum viable data and using it to make better business decisions.

What does this really mean?

Well, we are huge fans of the Lean movement and Eric Ries' Lean Startup. The central tenet of the Lean Startup is what Ries calls the 'minimum viable product' - the product (in its widest sense) that you can launch and then measure the effect and analyse feedback; most critically, you can then rapidly iterate or pivot.

Minimum viable data is based on this concept.

The focus is on defining the key business issue or question and then acquiring the data needed to answer the question or inform how you can implement a test to answer the question.

The key is to find the minimum viable data - it doesn't need to be perfect or exact data, just to inform a decision on whether to stick, twist and to enable you to measure the impact of that decision.

In most cases the data needed will already exist in a business. It just needs assimilating, to be made simple and applied to a business issue. The business issue can be at very strategic or very operational - the concept of minimum viable data delivers the right data at the right time to the right people so that they can make a better decision.

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This post was written by Simon Spyer

Co-founder & Insight Partner at Conduit, professional insight-monger, dad, lover of all sport and Spurs.

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