Data miner Featured

8:00pm EDT July 26, 2007
David Goetz invited an industry sales guru to Lewis-Goetz & Co. Inc. to address his sales force and got sold on a way to manage his business.

“We walked him through our warehouse, and he went to the sales conference, and he got up there, and, of course, everyone expected to hear, ‘You’ve done great things, your numbers are good,’ all of that,” says Goetz, the company’s president and CEO.

But it was anything but a backslapping, cheerleading session. Instead of telling the sales force how great it was doing, he kicked off the session by asking the salespeople why a prospective customer would want to buy from them instead of from a competitor.

The consultant exhorted the salespeople not to trust only their sales numbers and the compliments from their customers as the yardsticks for how they were performing, and he challenged them to measure things like on-time deliveries and fill rates. What doesn’t get measured doesn’t improve, he advised them.

The consultant’s message was like a splash of cold water because Lewis-Goetz was growing quickly and was profitable, and everyone was happy.

For Goetz, the session was an eye-opener. “I think that was probably an epiphany for me,” he says. Goetz knew that any inefficiencies the company was experiencing would grow as the company did. With a growth strategy based on acquisitions of other industrial distributors of hose, gaskets and belting products — its revenue grew from $90 million in 2004 to $177 million in 2006, with much of the growth attributable to acquisitions — Lewis-Goetz needed better ways to gauge performance and control costs.

On the sales side

While Goetz has been a strong believer in using data to drive decisions for a number of years, his former partner, who handled the sales side of the business, wasn’t nearly as enamored with a similar approach when it came to the sales function. But once his partner retired a half dozen years ago, Goetz decided to use sales data, with the help of software designed specifically to analyze it, to realign the sales organization to emphasize its focus and attention on servicing its large customers. First, he went about separating the small accounts from the large ones.

“Once he left, we reduced the total number of accounts that our outside folks were calling on,” Goetz says. “We wanted them to be more focused. Some of them had as many as 200 accounts that they were responsible for. Now, when you’re doing that, it’s a culture change, so what we did was said, ‘OK, we know you’re not calling on all these guys and the bottom 150 are small accounts. You’re going to make up for whatever volume is lost.’ So we actually got everybody down to 35 accounts. There was a little bit of grumbling, but we eased the pain with monthly bonuses that made up the difference.”

Additionally, Goetz used the data to balance its pricing so that small customers were charged to reflect the disproportionate cost of servicing smaller purchases. To find out what the true cost of selling to each customer was, Goetz used activity-based costing, a method that takes into consideration a variety of factors associated with an activity, such as manufacturing or selling a product. For example, the cost associated with performing functions like taking an order or generating an invoice are virtually the same for a $10 order as for a $10,000 order, making the smaller order proportionately more expensive to process.

“Through the activity-based costing model that we have, we were able to identify a couple of years ago, in our organization, customers that give us less than $5,000 a year in business and whether or not they’re profitable,” Goetz says. “By this time, we had 35,000 of those accounts at 20 locations. We said, ‘Look, the computer can tell us that these are the 35,000 accounts of less than $5,000 that cost us money. With the information we have, we can see we’re losing $1 million-plus on these accounts. Here’s what we intend to do on these accounts: We intend to raise the gross margin level to the point where they’re profitable. They’ll either leave because they think we’re charging too much, or they’ll be profitable because this is what it costs to service them.’”

But Goetz didn’t simply use the data to make indiscriminate cuts and establish blind policies regarding the size of accounts. Those affected inside the company had an opportunity to look over the list and suggest some exceptions.

“Before we did that, we had the customer service organization, the managers and the outside salespeople vet that list,” Goetz says. “There could be customers on that list that were $2,500 customers but had the potential to grow to $25,000. But if these guys are giving us all their business and it’s costing us to service them, let’s change the price. So we had total buy-in by everybody in the organization, as long as they had a chance to look at the list before this broad brushstroke went through the organization.”

While sales to the small accounts dropped, the company showed better profitability as a result.

“What we found was from one year to the next — at this time we were at about $102 million in sales — the total sales to these accounts was about $1.8 million,” Goetz says. “It dropped to about $1.2 million. The margin increase was significant, and the gross profit dollars were actually higher on lower sales. The number of transactions dropped from 8,500 to 2,500.

“What it did was it allowed us to service what was growing at that particular time as the economy was taking off. It allowed us to focus on the targeted accounts that we wanted to grow with, with the same work staff and not have to add people. So, it’s really cool when you have hard data to back you up. You bring in a bunch of people and you say, ‘This is what we’re talking about,’ and then you show them the results.”

Goetz also finds using data to be a powerfully persuasive tool in other parts of the business, as well.

“We create an income statement for every single location, and we allow every single location to see it,” Goetz says. “We show the company average of occupancy expense, travel and entertainment, all the different categories. Then we’ll highlight where expenses are in excess of the average. Then we’ll have a sit-down and do one-on-ones and ask why would that be; have them explain why it is, or we’ll help them understand why it is and help them get it more in line with what the rest of the company is doing.”

Making acquisitions

In making some of the company’s acquisitions, Goetz has used a model based on Lewis-Goetz’s performance metrics to predict the kind of performance that might be expected after the acquisitions are completed, thereby convincing lenders to bankroll the deals.

“We would take the metrics of our inventory turns, our day’s sales outstanding, our activity-based costing performance on improving overall profitability of the business, all of those metrics and say, ‘OK, if we can do half as good with this company in the first year as we do with this company now, here’s what the results would be,’” Goetz says. “So our pro forma includes taking our metrics and applying them to the target company and seeing what that does to the bottom line. If we combine it with our business, how does that translate into how fast we can pay off that loan? It’s pretty empirical; it’s data driven.”

And once Lewis-Goetz makes an acquisition, it compares its own data to the acquired company’s to make structural changes to bring it in line with its own practices and persuade management of the changes that need to be made. For example, after it made the acquisition of Goodall Rubber Co. in 2006, Goetz compared the acquired company’s performance to that of Lewis-Goetz.

“In 2005, they lost $700,000, and yet, they paid out $420,000 in bonuses,” Goetz says. “Again, hard data does it. When we brought their managers in, I showed them what our bottom line was, and I showed them what our bonus pool was. Our bottom line was low seven figures, and our bonus pool was lower than their $420,000. I said, ‘You’ve got this loss, and yet, you’ve paid out bonuses.’”

The data supported the notion that there needed to be an adjustment in the bonus arrangements that were in place.

“Our guys know these numbers and realized that it doesn’t make good sense to be paying bonuses when you’re losing money,” Goetz says. “So the variable compensation plans had to be changed.”

Goetz says using the data aggregated across its 48 locations will highlight clearly where extraordinary costs or expenses exist.

“It’s simple things,” Goetz says. “As we’ve done acquisitions over the years, we’ve seen people spend money on frivolous things or things they thought they needed, in some cases, entertainment. We’re not against entertainment, but we think it should be within a certain limit, and it’s getting them to understand it, as well. It’s part of doing business but not extravagant entertainment.”

Again, some discrimination is in order when it comes to applying the data. Goetz doesn’t use it as an excuse to slash such expenses indiscriminately. Salespeople used to entertaining clients at a certain level have to taper their expenses rather than cut them off abruptly.

“They have to be kind of weaned off it, as opposed to, ‘You can’t do it at all,’ and it’s on a case-by-case basis,” Goetz says.

But the data doesn’t always indicate that cuts are in order. Sometimes there’s evidence that not enough is being spent in particular areas. In the case of entertainment, for instance, it can indicate that there isn’t enough being spent to keep relationships lubricated.

Says Goetz: “There have been cases where we’ve had to encourage some to spend a little more.”

HOW TO REACH: Lewis-Goetz & Co. Inc.,