Instrumented Interconnecteds Intelligent

Doug Dow, Vice President, Business Analytics Transformation, IBM

By Doug Dow

As one veteran sports writer conceded recently, in the battle between gut instinct and algorithms: bet on “team calculator” every time.

From presidential politics to professional sports, sophisticated quantitative analysis is winning over experience and intuition. In business, organizations that have embedded analytics into their operations significantly outperform those who are still kicking the tires, according to a recent joint MIT Sloan Management Review and IBM Institute of Business Value study.

And yet, within many large organizations, the implementation of analytics remains highly uneven. For every organization that is playing “Moneyball,” there are more still puzzling over how to get started. The primary obstacle to widespread adoption: a “lack of understanding for how to use analytics to improve the business,” according to the Sloan study.  

Within IBM, we established an internal analytics practice several years ago.  Working with business leaders from across the company, we’ve deployed analytics projects in areas ranging from sales planning to product development, and from manufacturing to human resources.

As a result, we’ve made headway in our transformation to a smarter enterprise – and learned some practical lessons. As you build an analytics capability, here are a few principles to bear in mind:

1. Focus on the most important opportunities facing the business today. Driving revenue growth is at the top of IBM’s priorities. On this front, we have been creating and deploying new Web-based analytical tools to help our sales teams. Our math experts in IBM Research helped build these models which our reps use to predict purchasing patterns – and our sales managers use to better align sales resources in a specific territory. The tools have contributed to stronger revenue growth since we started our first sales prospecting analytics program six years ago. Initially, we had to persuade our sales leaders to pilot these analytical tools. Now they are coming to us, asking for more. They want to take it to the next level.

2. For each business opportunity, start with the questions, not the data. Begin by understanding your business strategy and financial objectives – target market, customer segments, business model and priorities. Then ask where the implementation and execution gaps are. How effective is the product or service development process? Which sales management processes need improvement? Where is the innovation occurring? From the right set of questions, it’s not hard to determine what data needs to be assembled and mined for insight.

3. Press your analytic experts to make their tools consumable. This is a point I stress with my team when we’re working with a business unit on an analytics projects. You shouldn’t require an advanced degree in mathematics or need to be well-schooled in Monte Carlo Simulation to find value from analytics tools. Web-based tools should be intuitive. With IBM’s Internal Business Analytics Cloud, internally called Blue Insight, we’re giving IBMers in different functions desktop access to advanced analytics. For example, our finance team can examine cash position forecasts or HR professionals can conduct an on-the-spot skills gap analysis, all from their browsers. The key is to pilot tools with the users so the data analysts are collaborating in a hands-on way with the business analysts who will be using the tools. 

4. Use data to find problems before they are problems. IBM currently has more than two dozen analytics projects underway in our integrated supply chain. We’re using analytics to reinvent traditional supply chain functions such as parts management. The Quality Early Warning System, for example, uses analytics to detect quality defects faster and earlier before they impact IBM products or clients. Analytics keep getting better, more predictive. 

5. My final advice:  don’t wait for your data to be perfect to get started. You can organize and “cleanse” data incrementally as projects progress. The key is to put a stake in the ground with a commitment that analytics will be woven into your strategy.

Big Data is here to stay – so embrace it, establish a link between your business priorities and your information agenda, then apply analytics to become a smarter enterprise.

To learn more, see Analytics: The New Path to Value.

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“start with the questions, not the data”. Very insightful! Thanks Doug-

Posted by: Wei Lee
December 13, 2012
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Doug, great article – we had a lot of experience in the Growth Markets where we started with the business problem and enabling execution of IBM’s 2015 roadmap.

I think we can also write about two more areas in the future: business Analytics and change management (our adoption challenges eg MAP) and business Analytics and social media – I have been researching this area and interviewed an intern this morning that write a paper on this topic.

Posted by: Maged Boctor
December 13, 2012
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Thanks Doug…very insightful. I also like your point of starting with understanding your business problem(s), model, and of course the enabling processes. Sometimes we jump to the details before understanding the larger picture.

Posted by: Roy Yoder
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Great Article Doug especially like 4 and 5 and that has been how we are leading many of our radical transformation projects. The data is never perfect. You have to start somewhere.

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Very informative Doug. The “start with the questions, not the data” part very much resonates with me. I think many people don’t get that fundamental idea and therefore don’t make progress with their analytics as fast as they could.

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