Big Data for Little Decisions, Day to Day Operations
By peterschutt on Jan 24, 2014
At the BIWA Summit 2014 (Business Intelligence, Warehousing, and Analytics), James Taylor, CEO and Principal Consultant of Decision Management Solutions, provided a provocative keynote on how to make Big Data practical, actionable, and operational.
As companies invest in Big Data infrastructure they are looking for ways to show a return on that data. Using business analytics to put this data to work improving decision-making is central to success. But which decisions should be the focus and how will you show improvement?
James discussed the importance of improving day-to-day operational decisions because of the largest scale and impact in front-line customer interactions across multiple channels on the web, in email, on mobile, in social, in call centers, in stores, in field sales or service. Strategic and tactical decisions are made less frequently and interactively and are riskier than front-line operational decisions where Big Data's velocity, volume, and variety is most relevant.
Key to powering more proactive decisions with Big Data is reducing decision latency from the time of an event to action with a better blend of human and machine decision making. Low decision latency requires automating front-line systems to be active participants, where as making people only more analytical does not have as much impact on day-to-day operations.
Begin with the outcome in mind then leverage Big Data in Decision Management Systems to test, learn, and adapt in production for quicker returns and better responses. Think in probabilities for new customer demand in marketing and sales, for reducing uncertainty, risk, and fraud in operations, and for improving the experience in service and support. The opportunity to democratize Big Data is in Little Decisions.