Big Data & Analytics Heroes: Richard Lee
“There will always be more data than we can use or manage,” says Richard Lee, this week’s IBM Big Data and Analytics Hero. “We simply need to understand what range of questions we are attempting to answer and size accordingly, while doing no harm to our ability to answer future questions yet imagined.”
What are the biggest challenges about getting started with big data and analytics?
One of the biggest challenges that I see is starting a big data and analytics program for the right reasons. If your leadership team does not understand the value and potential competitive advantage that come from becoming an “analytics-driven enterprise” then no level of tinkering within the business or IT department will ever get a formalized program established, much less supported over the long haul. I believe completely that the business must lead all big data and analytics activities (from strategy through execution) and that it is fully accountable for both the investment as well as the outcome. IT is then responsible to provide the necessary services and infrastructure to achieve the goals of each initiative. If you do not establish this dynamic up front then I do not believe you can be successful no matter how much money and technology you throw at the problem.
Other challenges can include: minimal cultural adoption based on insufficient change management activities, poor data and information management practices rendering all data and outcomes suspect or useless (no information governance), over reliance on technology and lack of sufficient analytical competencies at all levels of the organization.
What is the market still missing for big data and analytics to really deliver ROI?
The truly pervasive use of big data and analytics across the entire enterprise creates maximum leverage opportunities for each organization and will ensure that a maximum ROI (whatever metrics you want to use) can be achieved. However, we are still using big data and analytics in a selective and siloed fashion, and only achieve pockets of ROI, instead of the horizontal benefits that could be realized. There are two critical areas that must be addressed in order to overcome these shortcomings:
The senior executive team (and the board by extension) must have the knowledge and belief that big data and analytics are essential, even critical, to the organization in achieving its strategic, tactical and operational goals. They must drive this imperative from the top down and engage with the culture of their organization to embrace this philosophy, make it pervasive and not resist the changes associated with it.
- Senior execs and managers must raise their own game to become “big data and analytics-literate” such that they can foster the creation of new applications of information and analysis to surmount challenges and create opportunities, and then lead their teams to success in achieving their goals. We cannot continue to rely on internal centers of excellence and competency centers to act as a crutch for what should be within every executive and manager’s capability set.
Should tomorrow's generation acquire analytic skills no matter the degree? Why or why not?
When I got my MBA almost 30 years ago, decision science (part of decision support) was in its infancy as a discipline. Today, every manager and executive must have deep skills and acumen in informatics and analysis as part of their core capability set. This can be achieved through either undergraduate studies and post graduate education programs as well as via specialized and on the job education. Regardless of the path that one takes you should become skilled and competent early in your career, apply it often and grow your mastery over time. I see it as a life’s journey with new learnings each day.
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