I was recently reading Leveraging Big Data For Business Value by Harvey Koeppel on TechTarget and he lists the following five tips to jumpstart big data’s buisness value
1)If you’re not already, engage your leadership in conversations around what is happening and why it’s important to the enterprise, to your shareholders and to your customers;
2)Support your leadership in evolving their enterprise business strategy to adapt to and exploit these new business models and technologies and the big data capabilities that enable them;
3)Ensure that your information and data strategies and governance processes are aligned with your business strategies and models;
4)Manage these efforts as you would an agenda that supports innovation — small, short-term, incremental efforts that are manageable and that yield measurable and meaningful business results; and
5)Accept the fact that there will be failures along the way. Learn to recognize and learn from them so that the probability of success increases with subsequent iterations.
The whole article is really intriguing, but I was struck by the last point by accepting failure, especially as this is the second time this week I have come across this concept in the context of Information Management initiatives. The other place I came across with this in an AIIM Expert blog post by Daniel Antion entitled, Failure Should Be An Option. In it he states, “I no longer see success vs. failure as being binary in nature. Too many things today are moving too fast to lock in on a point in time, a set of attributes and a series of results and say ‘we have a success!’”
To use a sports analogy, (because I love sports and it is baseball season) no batter will ever go up to bat and have a perfect batting average throughout the season. A perfect example is the start of Willie Mays professional baseball career. In his first 12 bats he was 0 for 12. In at bat #13 he hit a home run of the legend and future Hall of Famer Warren Spahn and his career took off. In his 0 for 12 streak he may have looked like failure, but as more data came in that perception changed. That first 12 at bats snapshot does not give an accurate picture of Mays whole career. In today’s information age, you cannot compare a snapshot of data from today to a snapshot of data from 10 years ago because the accumulation of data is growing so quickly in today’s information age. Therefore, it is harder to use data to make a decision or gauge the success of a decision because it is harder to grasp our arms around big data.
In any information management initative there is risk and that risk is hard to gauge because the amount of information is not static, but instead it is growing at astronomical rates. Because of this, we have to be ok with risk and the potential for making the wrong decision. To cushion the blow of potential failure it is helpful to keep in mind what Dantion states about the low cost of wrong decisions, “the cost of making the wrong decision is decreasing, and may actually be lower than the cost of not deciding.”