Uncommon Insights: The Crunchy Questions That Lead to Deep Data Exploration

The frontier of business analytics is creating new possibilities to improve performance, identify growth opportunities and avoid risks. Analytics offers the uncommon insights that allow you to see beyond the data and move from “what I need to do” to “what I need to know.” Getting to those insights takes asking the right questions — or crunchy questions — that if you find the answer will move the needle for your business

Tune into this episode of Deloitte Insights to learn how business analytics can drive smarter decisions and better results.

Speakers

Jane Griffin, a principal with Deloitte Consulting LLP and Americas Deloitte Analytics leader

Tom Davenport, President’s Distinguished Professor in Management and Information Technology at Babson College and senior advisor, Deloitte Analytics, Deloitte Touche Tohmatsu Limited

Transcript 

Sean O’Grady, Host, Deloitte Insights: Hello and welcome to Insights. On this program, we are talking about business analytics and the crunchy questions that lead to deep data exploration. We are joined by two guests in the studio to analyze this topic and they are Jane Griffin, a principal in Deloitte Consulting LLP and Americas Deloitte Analytics leader and Tom Davenport, a senior adviser to Deloitte and a distinguished professor of Information Technology and Management at Babson College. He is also the author of several books on business analytics, his latest titled Analytics at Works: Smarter Decisions, Better Results. We are going to talk about those crunchy questions in just a moment. The first, what exactly is business analytics and how is it different from business intelligence, Tom?

Tom: Well, I define it as just the systematic use of data and quantitative analysis to make decisions. This intelligence was mostly about reporting whether it was standard reports every month or ad hoc reports or queries, business analytics is more about prediction, optimization and more sophisticated uses of mathematics and statistics.

Sean: How about you Jane, what is business analytics?

Jane: Well, business intelligence is about gaining the hindsight and insight into what is happening in the business and what do I about it. Business analytics is looking into the future to understand that my customer interaction, how am I going to improve it, understanding the profitability of a product line, and how I continue to extend that, understanding the risks in the market and how I respond to reputational risks or any other components that might jeopardize my success.

Sean: Jane, we are going to stick with you and my question is what is going on at the frontier with business analytics.

Jane: Well, it is a very popular topic today. Every client from the boardroom down to the frontlines wants to understand how they apply business analytics and all the information that we have gathered from all the different sources over the years to really make a difference in their business. So they are looking at that information asset frontier and are trying to apply it to everyday decision making and get better results.

Sean: Tom how about you, your view on the vanguard, the frontier.

Tom: Well, to me the vanguard is really industries that have historically not been analytical at all are really starting to change. You see it all over the place. Education, where you have student performance data; health care, where the U.S. government is spending literally billions to try to get every hospital in position to use electronic medical records, which is going to create massive amounts of analysis even to the point of identifying patients who may be coming down with a particular disease like diabetes, so you can head it off quickly. In manufacturing, you see areas like green manufacturing that were never using analytics before, they are putting sensors on things like windmill so you know when is the time and we should really service this windmill. Many of them are offshore, it is very expensive to go out in the water and service them. So if the sensor is telling you the failure pattern, it can save you a huge amount of money in terms of your maintenance expense.

Sean: Now, we have got two graphics for the audience to help them visualize this analytics process and the first is called analytics vision. Can you describe this chart and its components, Jane?

Jane: Well, there are really three basic components for business analytics, the first is information management. What facts do I need to track and what value does that data actually provide to the business. Performance optimization is the second. That is around looking at the history and how I have performed against my metrics and measures. Business analytic insight is the third and that is really looking to the future and asking those crunchy questions that I need to understand what opportunities I can take advantage of and what risk I need to avoid.

Sean: Tom, what is your take on this graphic?

Tom: Well, I think for me the most important thing of it is that all three of those steps are targeted to particular business problems and issues, so analytics is a really broad activity, we cannot analyze everything, so I think it is very critical to identify what are the real business questions that matter and focus the performance optimization and the forward-looking insights on the business questions that really count.

Sean: We got a second chart for the audience here that shows the steps for applying analytics. Jane, what are the steps and how do they help an organization master the discipline of analytics or adopt analytics culture?

Jane: Well, the first thing is to start from where you are. Assess your maturity in analytics and how you might be applying analytics cross the different business functions in your organization, whether that be merchandising or supply chain or work force, and whatever those disciplines are, so assess your maturity and start from where you are and build from there. Another one is to really look at the signals, understand not just the structure data that we have traditionally looked at with business intelligence but what are the new signals that are coming from click stream data RFID tags, asset intelligence like Tom mentioned with the windmills, what is social media saying about my products and my reputation, what’s my workforce opinion through wisdom of crowd, so looking at all of the signals when I ask that crunchy question and making sure that we are taking all of these into heart when making decisions.

Sean: Tom, your take on this graphic?

Tom: Well, to me the interesting thing about it is that it really has a bit strong focus on the decision to be made and the decision maker and you know just that idea of start where you are. I was talking recently to a marketer who asked me how about focus groups, does that count as analytics and I said well, on the one hand focus groups have largely been discredited, there is a well known tendency for participants to tell you what you want to hear; on the other hand I think it is not a starting point. You can get maybe more sophisticated from there and build on it and if your decision maker ultimately is somebody who is comfortable with focus groups and that is all they are comfortable with, you have to really stick with that to some degree, so I think you have to think about what is the intended audience and how is this information going to be used.

Sean: Did you have something over there?

Jane: Yeah, I just wanted to add social media is a hot topic today and many of our clients who are in the product business, especially consumer products, are listening to blogs and social media for diagnosis of issues that relate to their product and they are correcting them before the call center ever hears from a client about an issue. So you can look at the signal based on the question that you are asking and really get new insight and immediate action that can change the way a product is perceived or adopted.

Sean: I actually want to go back on something you said and it is the title of this podcast and it is crunchy questions. What is the crunchy question and how do they help an organization focus on the right analytical pursuit. Tom what is a crunchy question?

Tom: Well, things that crunch, I guess, or things that you can bite into and so you are looking for questions that you can really bite into, that are serious, substantive, important to your business. If you find the answer, it will really move the needle on your performance, questions on which you can actually get some data. It is hard to do analytics without data, so if you cannot gather any data, you might want to look for some other crunchy questions and then I think finally it is questions that are going to lead to action. I was talking to the head of a commercial analytics group at a pharmaceutical firm and he said you know, people come to ask us whether we can do promotion analysis. Are our promotions working? Now that is a crunchy question but he answers in a sort of crunchy way. He says we can find out three possible things here, either it is a fantastic successful promotion, either it is marginally successful, or it is unsuccessful. What are you going to do in each one of those cases? That sounds a little cheeky but it puts the emphasis on what action are you going to take on the basis of the analytics that they perform.

Sean: How about you Jane, you like crunchy questions?

Jane: Absolutely, and one of the key things about a crunchy question is I have to look at the business process to make sure that I take the question and actually implement. If I have come up with a new pricing scheme by product, by distribution channel, I might need to change my compensation system, my sales force compensation. I may need to link inventory information with this new pricing model to ensure its inventory levels go up and down that I am tweaking that model, so crunchy questions or asking the ones that are actionable in informing my decision but also monitoring and improving the processes in the business is all about weaving it together.

Sean: So my last question for you. Hopefully, it is a crunchy one, and that is what does your company has been doing right now, Tom?

Tom: Well, my great passion, Sean, is that they should be kind analytics to the actual decisions that they need to make. You know, identifying what are their key decisions, trying to figure out which ones need some help, which ones need to be improved, and then applying several interventions. Analytics in my research are the most common interventions but you also find that they are typically applying changes in culture and leadership to improve their decision-making, educating frontline people, changing the whole decision process, so analytics are really only one intervention that organizations need to make. They need to be done in concert.

Sean: Jane, your final thoughts?

Jane: Well, analytics is about putting the right information in the hands of people where it matters. On the frontline, if I am dealing with a customer, I should know what your expectations are and what is the next best offer I should make to you is. In the strategy room and the boardroom of a company, you should look at your strategy and understand what the risk of not achieving it or the opportunities that you are missing with analytics and how I weave that into my decision making. So it is moving from an intuition-based culture to a fact-based culture where the facts really matter.

Sean: So if you can measure it, you can improve it. We have been talking analytics with Jane Griffin, a Principal in Deloitte Consulting LLP and Tom Davenport of Babson College and the author of Analytics at Works: Smarter Decisions, Better Results. If you would like to learn more about Jane, Tom, or any of the topics we discussed on this broadcast, you can find them and many more on our Web site. It is www.deloitte.com/us/podcasts. For all the good folks here at insights I am Sean O’ Grady. We will see you next time.