Business leaders face myriad decisions every day: How can my company be more efficient? What strategies should we use to exceed our customers’ expectations? Can we predict what our market will do?
Data and information provide the clues to answering these types of questions and others that affect a company’s strategic position.
Leaders who regularly employ “data-driven decision making” tend to make better decisions over the long run. However, companies are realizing that there is more data available than that in their traditional data warehouse. In fact, data are coming in so fast from sources such as social media and real-time markets that companies realize that they need a data strategy itself to just stay even with the competition.
Generally, the term “big data” refers to data that have one or more of the three Vs: volume, velocity, variety. That is, there is a lot of it, it comes in fast and it can be of many different types, such as written language or images. Big data isn’t found in your traditional data warehouse. You might be able to use it if you can figure out how to capture, store and analyze it.
But first, why should you care?
There are many examples of companies gaining sustainable competitive advantage through analyzing big data, i.e., analytics.
Progressive Insurance is able to drill down to small customer segments to predict risk and set more accurate pricing in the market. Harrah’s predicts customer response at the individual level with insight into effective marketing. Marriott determines optimal room price dynamically. Walmart and Amazon use insight into their supply chains to reduce inventory and stock-outs, and UPS predicts customer churn to get ahead of competitor offers. There is evidence that data-driven companies perform significantly better on both financial and operational measures.
How Can You Use It?
Traditionally, online retailers have been able to suggest new products to customers based on comparing what they bought and what others like them bought. However, you also can discover from your web site what your customers browsed, how long they stayed on any page and what they clicked on. You can track their reactions to suggestions, their response to dynamically-generated promotions and the influence of their reviews on your and others’ sites.
Data outside your company, called “external data,” can be queried from social networks and blog sites for customer opinions and sentiments.
All of this big data and its analysis do more than answer the question: What will this customer buy next? It changes the questions themselves to: What is the potential value of this customer? How influential is this person? How should we communicate with him or her, and which channel should we use to build a long-term relationship? How can we engage with this person through products and services that the customer has not yet thought of?
So how can you get started with big data and analytics? Here are some suggestions.
1. Align your business strategy with your data strategy.
One of the first steps is for the management team to create a vision of how big data and analytics can help the company, asking such questions as: “What questions do we want to answer? How can these new sources of data help us with our business strategy? What are our priorities?”
2. Develop a realistic investment strategy.
A company can invest in big data and analytics at any level, and there are specialized tools that make it fairly easy. But these tools are dependent on having a smart user. So a company needs to determine if it has the necessary human talent to help it envision the possibilities.
Once talent is in place, new opportunities will arise naturally. Start small, realizing that the various skill sets needed to effectively utilize big data in a big way for business decisions may require a team.
3. Anticipate the change management issues that will arise.
A big data strategy raises questions such as who owns data in a company, are the data accurate, how have decisions been made and who makes them, how will new insights from big data be used to change or modify decisions, and how will conflicts that arise be managed.
Since a company will want to see a return on the big data investment, there is a danger of moving too fast without buy-in from internal stakeholders.
4. Develop the skills and training of the entire organization.
Big data and analytics is more than a single person or team coming up with new insights. It is a way of doing business and making decisions. The best approaches combine insights from the big data analysis team with the experience and professionalism of the entire company.
The organization needs to be actively engaged in asking the right questions, challenging results that aren’t consistent with experience and integrating information from various sources. New incentives may be needed, and frontline managers may need training to infuse analytics into their decision making.
It is clear that big data and analytics will be increasingly used to guide business decisions in the future. The nature of questions that can be answered will change along with business models, the nature of expertise, the value of experience, business processes and the decisions made. The data revolution has started.
Gloria Phillips-Wren is professor and chair of information systems and operations management for Loyola’s Sellinger School of Business, which has a campus in Columbia. She can be reached at firstname.lastname@example.org.