MDM recently spoke with Tony Pericle, author of Transforming Data into Action: Using Analytics for Better Distributor Sales Decisions from the National Association of Wholesaler-Distributors. This is part 2 of that interview. Part 1 was published in the March 10, 2012, issue of MDM. In part 2, Pericle says analytics alone won’t solve all problems. It takes ongoing course correction and the “common sense test” to get the best results from any effort to use data to make better decisions for your organization.
MDM: When defining analytics, you include walking around the company and getting more qualitative information. That is just the first level of nine you outline in your book. Do companies sometimes think too narrowly when they think about how to use data to improve their organizations?
Tony Pericle: If you think you’re going to be able to use data to answer all of your questions, you are absolutely wrong. I’ll use this example. I have five children and I’ve taught three of them to drive so far. Now I am teaching a fourth one. I take him to an empty parking lot, and I have a crunched Aquafina bottle that I throw out in the parking lot. I tell him: “I want you to drive over it with your left wheel. And then I want you to drive over it with the right wheel.”
What’s interesting is when a teenager gets behind that wheel, they want to keep that wheel as locked as possible because they think that by keeping that wheel so it’s not moving, they’re going to go straight. However, roads are not always straight so one must constantly course-correct based upon the landscape. That’s what driving is all about. Companies strategically set a course in one direction, let’s say due North. Over time, storms arise and threaten to throw a company off course.
Analytics can both provide advanced warning of an impending storm and identify alternative paths around a storm. Companies need to constantly monitor the landscape ahead and course-correct when necessary or risk ending up in the wrong place.
The story is told that, going to the moon, if they’re off by 1/100 of a percent, they are going to be thousands of miles away from the moon. When you make a decision using analytics, you can bet that if you did it right, you did not go in the right direction. The wind is going to pick up stronger than you anticipated; you’re going to be pushed off-course somehow. You need to be able to measure your performance and then make a course correction.
That’s what analytics is all about. It’s not about, “Here’s the perfect price,” or, “Here’s the perfect way of doing something.” Analytics is about giving people guidance.
MDM: How can personal interaction and data work together?
Pericle: There are two anecdotes here. I liked the phrase a co-worker of mine used. He said, “Tony, after you’re done with your analysis, we need to determine if it passes the ‘Does it make sense?’ test.” I’ve used that ever since.
I realize that I’m going to miss some things. Reviewing an analysis with peers, business owners, field sales, etc., allows the group to challenge the results of the “Analysis” within the context of the real world.
There are often some things that I included in the analysis that I should have excluded or considered in a different way. You have to allow interaction between people to look at the analysis from a practical perspective.
The other point I wanted to make is if you hire an analyst, don’t expect ground-breaking ideas. Most often, good ideas will come from somebody that is involved in the day-to-day, and the job of the analyst is to listen, to ask questions, listen again, and then listen some more. And then to be able to say, “Okay, how can I support this idea with hard data? What could be done to enhance or improve on the idea? What can I do to help the business move this idea forward?”
There are hundreds of great ideas within any given company. There are probably five of those hundreds of great ideas that if somebody just listened, would have a monumental impact for that company in terms of revenue, margin, or both. Opportunities are all around us. It’s just a matter of uncovering those opportunities.
MDM: At what size company does it make sense to invest in these tools?
Pericle: If you’re talking about a $3 million company, you probably have no more than two sales reps. You probably have a president of the company who has met with the customers that represent 70 percent of the overall volume. The need for a full-time “analyst” is not that great.
A better option would be to ensure you can display and analyze information in a meaningful manner. If you don’t have timely, relevant, and easy access to data, think about outsourcing this task to a third party, much like you may do with some operational tasks today.
Groundbreaking events will arise from what the “core” team in a small company can learn from the data. Analytics fits in where you come to a point where your brain just can’t handle more than 500 unique customer item combinations. If someone says, “I have a $3 million territory and each customer buys 100 unique items from me, and I have 200 customers,” it is highly unlikely that any one person can truly optimize every decision. For example, shortcuts may be taken around pricing because it’s too much work to actually measure what the market will bear for any given item.
It’s easier and safer to leave things where they are, but the downside is money left on the table.
Analytics could identify pockets of low-risk, high-margin pricing opportunities leading to increased margin and a more optimized price.
Tony Pericle’s book, Transforming Data into Action: Using Analytics for Better Sales Decisions, can be ordered at www.naw.org/transformingdata or by calling (202) 872-0885. Pericle, the founder and principal analyst for ProfitOptics, can be reached at firstname.lastname@example.org.
In his book, Transforming Data into Action, Tony Pericle defined nine ascending levels of analytics and examples of the questions each answers. The lower levels (starting at 1) are descriptive, and the higher levels are what Pericle calls prescriptive. The first three are commonly executed by distributors, he says, some do Nos. 4-5 and very few have the necessary tools to do the rest.
1: Personal Interaction– “What’s going on? Are there any problems?”
2: Reports – “How did we do? How many problems did we have?”
3: Ad Hoc Analysis– “What were the details?”
4: Drill-Through Analysis– “Who, what, where, and when?”
5: Guided Drill-Through Analysis– “Where do I go next to see what is most important?”
6: Driver Analysis – “Where are the key variances in my business? What are the microsegments of my business I should focus on?”
7: Science (Advanced Mathematical Modeling) – “Are the differences significant or are variations due to randomness? What’s the optimal choice?”
8: Alerts– “Is there something I need to focus my attention on now?”
9: Proactive Alerts (Forecasting)– “What do I need to do now? Where will opportunities exist?”