Integrating BI and MI for Big Data Decision Making

Jun 25, 2014


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Article ImageBusiness intelligence focuses on internal data. It's the information that companies have stored in data warehouses including financial, pricing and customer information. It's used to look for clues about effectiveness, efficiency and productivity and how it can optimize business processes.

Market intelligence (also known as competitive intelligence), is more about looking externally at market conditions, trends, opportunities and threats; as well as at the competition, market shares, penetration strategies and go-to market models.

While both are needed in order to run a business, traditionally, organizations have looked at BI and MI separately. However, given the big data movement happening today, it's becoming more important to combine both sets of data in order to get the complete picture of what's happening both internally and externally with an organization.

Separately, BI and MI provide only half of the picture. Used appropriately, market intelligence can provide context for business intelligence. Joost Drieman, vice president of Intelligence Best Practices at Global Intelligence Alliance compares it to driving a car: "Your dashboard is like business intelligence data, it gives you a very good idea of how effective and how efficient your car is running. Your windshield is your view of the world [market intelligence]."

He adds, "You cannot drive a car by just looking at your dashboard and you cannot drive your car just by looking through your windshield. It's the same in business. You may see through your windshield a market opportunity, it is not enough to say, ‘Hey, we have a great opportunity here so let's go for it.' You also need to look at internal data to determine if you're capable of doing it." BI will tell if you have the right resources, tools, assets and processes in place to execute.

According to Vijay Khatri co-director of the Institute for Business Analytics in the Indiana University Kelley School of Business, integrating both BI and MI for better decision making has its challenges. He says, "There are differences with data quality. Your market intelligence data may not be as timely as your internal data. The accuracy differences may be high too. You have so much more control over the accuracy of your business intelligence data. However, it really is about making business decisions in the context of having imperfect information."

Frank Acito, co-director of the Institute for Business Analytics adds, "Timing issues are really difficult and you have to work to synchronize them. If a manufacturing firm is sending shipments out the door weeks or months before the sales actually happen in the marketplace, business decisions sometimes get out of sync and production is ramped up at the wrong times when demand is going down and vice versa. So integration is not a seamless process."

Today, big data is largely driven by external sources such as social media, which can be a good gauge for market intelligence, providing insight into how customers perceive your products and what kinds of opinions they hold about you compared to your competition.

"One of the challenges is with our English language and the way we use it," according to Acito. "We can use sarcasm and irony and computers can't. They tend to take everything literally and if there are double negatives in a sentence, they get confused. People are working to figure that out but that really makes it hard to make sense out of some big data."

Drieman believes that this is only the first wave of big data. "We started with just mainframe computers. We went to PCs starting to connect people and we are now connecting people through smart phones and tablets. The next stage is the Internet of Things where we start to connect devices. We expect in the coming five to 10 years that about 50 to 100 billion objects will be connected." These connected devices will generate data that can be used for customer insights, market insights and business intelligence purposes.

Drieman adds, "Twenty-five years ago, the main complaint was that ‘I don't have enough data' and today, the major complaint is ‘I have way too much data'. Data is now available to every person in an instant so the smarter we can read and analyze the data and use it to our benefit, the better our competitive advantage will be."

(Image courtesy of Shutterstock.)