Have you ever interviewed a someone who says they have “no metrics” for your case study?
Perhaps your source never had to justify their purchase, so they didn’t keep any formal metrics.
That means they have no numbers to show how much your offering helped with their business problems… and no numbers you can use in your case study.
Whether you’re a writer or a marketing manager, that’s not what you want to hear. Fortunately, there’s something you can do about it.
When this happens to me, I often start a line of questioning I call, “Is it bigger than a breadbox?”
This question was first popularized by Steve Allen on the American game show “What’s My Line?”
It’s a classic from “20 Questions.” And it’s still handy today, any time you have to interview someone who says they have “no metrics.”
Knowing that something is bigger or smaller than something else helps narrow the field of possibilities. This line of questioning leads your source through some back-of-the-envelope calculations.
This article shows a typical example of playing the game and the metrics you can derive from it.
And there’s a bonus tip on how to convert from one metric to another to make your results more meaningful to your audience.
A typical conversation with a source
Perhaps our discussion starts like this. My source says, “We’re saving a lot of time now!”
So I ask, “How much time, would you say?”
When they say they don’t know, and they never kept track, I ask, “Well, how many people work in your warehouse?”
They say 20 on days, 15 on nights.
“So that’s 35 full-time people in the warehouse?”
“Yes,” they confirm.
“And was it always that number?”
“Oh no, before the new system we had more. We’ve been able to put some people on days, which they prefer. And we re-allocated some people to other jobs. And we let go a few poor performers.”
This is when you help guide their reasoning.
“Okay, so how many people did you re-allocate? And how many did you let go?”
“I think 4 we re-allocated, and 3 we let go.”
“So you need 7 fewer people in the warehouse now? And you can still handle the same number of orders?”
“Oh no, we’re doing more orders with fewer people. Let me check…” They take a minute to look up a report on their screen. “Yeah, we’re doing about 20% more orders with seven fewer people.”
“Wow, that’s great!” I say.
“Yeah, as I told you, we’re pretty happy about that.”
“Well, let’s see if we can develop that a little. So, what’s the typical wage for a warehouse person there?”
“Well, that varies all over the map. They can make bonuses. And we pay a premium for working nights.”
Playing hi-low to get another metric
When your source says there’s no “average” value, because the numbers fall over such a vast range, you can use a variation of the “breadbox” question.
You can call this version “Hi-Low.” Ask your source for the highest and lowest values, and then ask what would be about the middle. Here’s how it works.
“Well, if I asked for the absolute lowest and the highest possible max, what would the range be?”
“Well, I’d say a day guy who really doesn’t push it very hard, he’s making $35,000. And a real go-getter at night who picks and packs faster than anybody, he could reach close to $50K with all his bonuses.”
“Okay, so the range is $35 to $50K. That totals $85 divided by 2, let’s see, umm… that $42.5K average. If we say your average warehouse worker makes $40K, does that sound about right?”
“Hmmm… well, most guys push it on this job. They love the bonuses, and they come in on Saturdays if we need. I’d say we could stick to $42.5K average.”
“Great, thanks. So we already figured out you have 7 fewer people in the warehouse. At $42.5K each, that’s a savings of what… $297,500. Wow, that’s like $300K a year!”
“Gee, I never looked at it like that before. I gotta tell my boss! That system will pay for itself inside of a year!”
Don’t forget overhead
But the game isn’t over yet.
Don’t forget the overhead for every worker: things like payroll taxes, insurance, the cost of utilities like power and air conditioning. Ask about that too.
“And there’s got to be an overhead factor for every worker, right?” I ask. “To cover all the payroll taxes, benefits, insurance, utilities and all that kind of stuff?”
“Sure. We use a conservative number, so it’s not actually fully loaded,” they say. “Like at the warehouse, we don’t have to pay for planting flowers or buying desks or the stuff they need for the office.”
“That sounds sensible. So what number do you use?”
“We use $7,500 per worker per year. Just to keep it simple.”
“Ok, so that adds another $7.5K times 7 to our savings, right?”
“Yeah. I’ve got a calculator here,” they offer. Often they want to see the numbers for themselves. “So that’s another $52,500 in savings. At least.”
“Okay, thanks,” I say. And then I add it all up. “So we have savings on labor of $297,500 plus savings on overhead of $52,500 which equals… $350,000 on the button. Wow.”
“That’s over a third of a million dollars!” they chortle.
Confirming the bottom line
“You’re right, it is! Congratulations!”
“Well, it was the new system that did it. Just like I hoped it would,” they say.
“So can we put in the story that you’re saving $350,000 a year on labor in the warehouse?”
“Sure! And the best thing is, we’re getting more orders out. Another reason is we have fewer guys cluttering up the aisles, getting in each other’s way and slowing down the forklifts. So the new system is giving us all kinds of benefits that help the warehouse run faster and smoother.”
So you can see how, in five or ten minutes of interview time, we went from “no metrics” to an impressive number on labor savings.
Documenting the new metric
After the call, I like to jot down our reasoning in a quick e-mail to my source. This gives us both a record, so we won’t forget where that number came from.
My source often forwards that e-mail to their manager as well. And I send it to my client as backup for that metric.
Bonus tip: Translating one metric to another
You can translate one metric into another that may be more meaningful to the outside world.
Just remember not to stretch the truth. Your business readers are not gullible. Some of them have MBAs. Some of them work in Finance. They can sniff out shoddy statistics.
How else could you express that $350,000 savings on labor? Here are three more possibilities.
Another way you could express your new metric is to say the warehouse reduced its headcount by 7.
As a percentage, that’s 7 out of the former total of 35 workers, or 20% reduction in labor.
Number of orders per worker
You could take the number of orders divided by 35 warehouse people before the new system. That would show the average number of orders filled per worker: a measure of productivity.
Then take the bigger number of orders divided by only 28 people after the new system.
Compare the two numbers. The new number is bound to be higher than the old.
Time to fill an order
Ask your source for the total number of hours in a week. If you need to, play hi-low to get the number of hours a typical workers puts in.
Then multiply a week’s worth of hours by 35 workers to find the total number of hours worked before. Divide that by the average number of orders filled in a week before. You’ll get the average amount of time it used to take to fill an order.
Then you could do similar calculations for 28 workers and the number of orders after the new system arrived.
Compare the two numbers. The new number is bound to be lower than the old.
So there you have it: a handful of new metrics from a source who said they had none. And you can get them all by playing “Is it bigger than a breadbox?” for a few minutes during an interview.
Do you have any tips to share on how to get solid evidence from a source? Please leave a Comment below.