New solutions for a new world

In his 30-year career at The Dow Chemical Company, Chief Information Officer Dave Kepler has seen upheavals in technology, the chemical industry and global markets – and has helped the company successfully navigate these massive changes.

"If you think of the mega-trends impacting the chemical industry, the first is the customer, driven by their consumers – and that's shifting where our company needs to be positioned around the world. The need for new sustainable products is shifting our business focus as well," Kepler explains. "We're moving from a company that was really focused on execution around product to one that's engaged with the customer, looking at new solutions for them and therefore solving some of the big challenges of the world."

That shift has helped the company grow to $53 billion in revenue, despite the lingering global financial doldrums. One of the keys to its success? "Analytics has really helped us in markets where we're trying to predict where the demand's going," says Kepler.

"Our historical patterns are changing. We need to use analytics to bring multiple variants in, aside from (historical) supply and demand patterns, to understand and predict demand," says Kepler, describing the company's tactical shift.

Becoming an analytical organization
As an organization of engineers and scientists, Dow has always valued data, but several years ago Kepler recognized that the company's analytical efforts were too internally focused. "We started out collecting data from our process systems or our research and we still use basic analytical tools to solve problems," says Kepler. "But we needed to apply advanced analytics to information from both inside and outside the company to detect complex patterns and trends that would help us find and capitalize on new markets and opportunities.

"To me, that's what an analytical organization is: one that focuses on internal and external information – not just relying on the experience and history of the past," says Kepler. "Doing that in a few key areas showed the value of analytical tools and techniques, and created a base we could build on."

Out of those early analytical successes, Kepler built the Business Services Group; one of its attributes is a centralized group of analytic experts who are a resource for all of Dow. When any department at Dow has a complex problem in need of analysis, it comes to Business Services for answers. 

"In addition to embedding individual analysts into business units across five portfolios, we built a core analytic group that can extend and enhance this expertise across all areas of the company – research, supply chain operations, manufacturing, marketing – bringing the right skills to help the business unit make better decisions," says Kepler.

"We ask questions like how big and complex is the information set you're working from? How much experience do people in this space have working with information? Sometimes modeling and other projects fail because you just don't understand holistically how to approach the problem. Most of analytics involves working with large sets of equations and data; you need to make sure collectively you get the right equations on the table to work on," he explains.

Measuring success
Kepler's approach requires employees to approach data differently, but the results have been strong. Every project Dow has applied analytics to has shown significant improvement. Those projects include:

• Enhanced sales forecasts. One hundred percent of the projects done using advanced analytics have significantly reduced forecasting error.
  
• Aggressive energy consumption reduction. The company has saved $9 billion in energy costs since 1994.
  
• Early insight for business units. By day 12 of every month, units know if they will make targets and can adjust strategy accordingly.
  
• Quick response to deteriorating economic conditions. The Business Services Group pushes critical information to business units daily.
  
• Deep insight into the role exchange rates play in margin. Dow developed regional exchange rate risk models to help make decisions about where raw materials are purchased and pricing for finished goods.
  
• Keen understanding of staffing levels. A human resources supply/demand model helps the company hire just the right talent at the right time.
  

"We can go back and show billions of dollars of savings," Kepler says. "And it helps with margin expansion. It's all about how we can be in the market with the right product at the right time and get focused on that, and then go back and measure our success, model future success and predict what we need to do next."

Kepler's words of wisdom
Change is constant and never comes easy – and in a company like Dow that's been successful for more than 100 years, resistance to changing what's worked in the past is especially strong. But, as Kepler points out, "What your company's done in the past isn't necessarily going to work in the next decade. Our shift from a product-oriented company to focusing on solutions required us to think differently about analytics. We had to move our focus away from just our operations and manufacturing into more exposure to markets, customers and external dynamics," he says.

In his years at Dow, Kepler observed that the success or failure of new technology was rarely attributed to the technology. More important was the way the technology was introduced. His advice to companies seeking to become more analytical, or introduce any new technology, is to focus on training, setting metrics for success and communicating what the new tools can do.

Kepler also has a list of criteria he applies to determine when new technology makes sense and when it doesn't. "There are four success factors. One, is there a clear strategic alignment with what the company's trying to do? Two, does senior leadership get it? Three, do you have the right program structure in terms of project managers, leadership, subject matter experts to implement it? And four, do you have a good benefit story that you're going to measure and track? If you've got those four components, you probably have a successful project."

As for next steps? Kepler affirms that Dow needs analytics to stay ahead. "The competitive advantage that companies are going to have going forward is making better decisions than other companies," says Kepler. "How you collect data and how you make decisions off that data is what's going to differentiate you from your competition. In the next 10 to 20 years, businesses that know how to harvest and use that information will be in the forefront. And we want to be at the forefront."

The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.

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