What happens if your Big Data analysis project tells you that your strategy for approaching the market is wrong? What if sentiment analysis of the tweet stream reveals that your latest product bundling is missing the mark? Can you react? Can you adjust in time to take advantage of these insights? In short, is your company agile enough to take advantage of what you might uncover?
The distractions brought on by the hype around Big Data need to be put in the right perspective. Big Data may yield big results, but the jury is still out on how organizations can bets reap the benefits. At worst, I think that the renewed focus on predictive analytics and data-centric decision making is a great bi-product of the Big Data phenomenon. We’ve started down this path before – many times, but haven’t seen it through. My hope is that the hype of Big Data will drive us further down that road and not leave us sitting by the roadside waiting for the next bandwagon to come along.
Much like decision support, data warehousing, business intelligence etc. etc. etc. were supposed to do, Big Data is supposed to help organizations improve business performance and gain competitive advantage. None of these approaches/disciplines can be advantageous if you can’t adapt based on the information they provide. Adaptation can only be realized if your enterprise is able to embrace agility and change. It takes commitment, not experimentation.
Agile doesn’t just apply to your system development methodology. It extends to all cultural aspects of your organization. Are your business processes flexible enough to account for rapid changes in direction? Are your supply chain insights deep enough to ensure that you can ramp up or down to meet demand when necessary? Are your management practices open to input from new data that may alter the tactics that are in place to meet strategic objectives? Can your analytics infrastructure meet the pace of change required to match the cadence of your business?
Here’s an oxymoron for you – you need a “solid foundation in agility” in order to consume and extract value from data-centric decision making. The sources of information which fuel insights are irrelevant – though Big Data certainly compounds the problem. Highly structured organizations with too much rigidity built into their DNA are not amenable to rapid change. These organizations will not see the degree of benefit from data analytics as more adaptable, agile ones. Modeling, analyzing, refining, and taking action must happen quickly, without hesitation in order to outpace competitors.
To paraphrase Darwin “it’s not the strongest or smartest that survive. It’s the most adaptable.” And adaptability requires a culture of agility.