| | January 201519CIOReviewscarce, so make sure you get a few `strong' people who understand this well. Have them establish organizational maturity around these concepts and help draft an organizational construct and a governance process to ensure alignment at the top· Start small, preferably with a well-defined problem. Make sure to articulate what you want as an end result before you start so there is no ambiguity about what constitutes success. Big Data is riddled with small data problems. You will discover that you have to take care of small data problems before you get to those BIG insights you were promised. Don't take short cuts!· Technology isn't the biggest issue, so maintain flexibility in the framework. You may end up with several technologies and that is fine. Resist the urge to consolidate prematurely. The whole field is so fluid that it will be a long while before any clear winners emerge. Aim for user friendliness. The more the users of the system, the better the chances of long term success· Establish depth for insights--most times, I notice that the depth of insights improve significantly over time. You need functional leaders spending quality time listening to the work and mentoring the team to dig deeper and helping them with their thinking. The move from casual to causal will take time, so patience is a virtue in this regard· Establish a governance process--a lot of functional organizations have a lot of data--from Manufacturing to Marketing, Technology to Product Management. It is ok for people to work across a bunch of problems in their functional silos, but ensure there is a good governance model to surface best practices and ensure exchange of ideas and people. This is tricky and can get political--nip it in the bud, ensure strong leaders help manage this by putting the organizational interests ahead of building fiefdoms· Lastly, don't be afraid to fail and do over, it will require many tries before you settle on something close to a `final' solution. The key is to ensure you don't lose a lot of money to get there. Establish metrics like `Time to value' so you can evaluate objectively how much effort is required to generate value.Data and Social/ Digital Marketing concepts are becoming mainstream that include concepts like Segmentation and Predictive selling, Behavioral Marketing, Social Monitoring for large scale trends and pulling out specific messages and insights and leveraging machine level data to do a better job of streamlining quality and manufacturing issues"Ajit Sivadasan
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