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How to Get More Value Out of Your Data Analysts
December 5, 2013 Editor 0
Organizations succeed with analytics only when good data and insightful models are put to regular and productive use by business people in their decisions and their work. We don’t declare victory when a great model or application is developed – only when it’s being used to improve business performance and create new value.
If you want to put analytics to work and build a more analytical organization, you need two cadres of employees:
- Analytics professionals to mine and prepare data, perform statistical operations, build models, and program the surrounding business applications.
- Analytical business people who are ready, able, and eager to use better information and analyses in their work, as well as to work with the professionals on analytics projects.
In Analytics at Work, we call the latter group “ analytical amateurs.” That doesn’t mean amateurish – only that you’re not a professional, that analytics isn’t your main occupation. You can be a scratch golfer or ace tennis player while still an amateur. Amateurs can be very accomplished analytically – in using analytical applications, envisioning additional opportunities for using analytics, and participating as business staff on analytics projects. You’re in luck if your CEO, executive team, and general managers across the business are all accomplished analytical amateurs.
There is widespread recognition of the shortage of analytical professionals. Lesser appreciated is the fact that most organizations are also way short on analytical amateurs. A May 2011 McKinsey Global Institute study on big data analytics predicted a coming shortfall of around 150,000 people with deep analytical skills – and a shortfall of 1.5 million business people with the know-how to put big data analytics to use.
The key to overcoming these shortages is to develop talent in both cadres together. In other words, the most important question may not be, “How can we hire more analysts?” But rather, “How can our analytical professionals best work together with our business people?”
The most effective employee development happens on-the-job, day-to-day, often one-on-one. The way to expand the business acumen of analytics professionals is to have them spend plenty of time working with business colleagues. The way to expand the analytical capability and appetite of analytical amateurs (a.k.a., business managers and professionals) is to have them work directly with analytics professionals on both analytics projects and simply meeting their own information needs.
By spending time “in the field,” professional analysts gain greater familiarity with business operations and pragmatic appreciation for how analytics are used in management decisions and employee workflows. What do the business people learn?
- To be more aware of the data they use and their own decision processes. They get better at evaluating and improving their data and adjusting their decision processes depending on the quality and sufficiency of data at hand.
- To serve themselves with data and analyses. They become more adept at finding data and using business intelligence and visual analytics tools, more rigorous in using established tools like spreadsheets, and thus better able to meet many of their analytical needs independently and immediately.
- To understand the logic and methods behind the analytical models, applications, and outputs they use. Will they pick up some statistical methods? Perhaps, but the real goal is to learn enough to understand and trust their analytics – and develop a sense of the limitations of analytics.
Analytical amateurs accomplished in these ways not only make better use of analytics in their decisions and work, but also make greater contributions when serving as subject matter experts or otherwise participating in analytics development initiatives.
In analytical organizations such as Procter & Gamble, professional analysts spend a lot of time in the field, including “embedded” in business units. And there’s an active rotation program getting business people into analytical roles (many of which don’t require PhDs in statistics or deep data scientist skills). Analyst talent may be in short supply, but the solution is to kill two birds with one stone and develop the two cadres together.
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