The Dashboard Effect

The KPIs You're Overlooking: Better Data Insights for Manufacturers

• Brick Thompson, Jon Thompson, Caleb Ochs • Episode 118

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In this episode, Caleb and Kate discuss important KPIs for the manufacturing industry. While there are no one-size-fits-all solutions, they outline and provide insight on the leading and lagging KPIs that have helped our midmarket manufacturing clients improve sales operations, inventory management, labor and machine utilization, and cash flow.

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Blue Margin increases enterprise value for PE-backed, mid-market companies by serving as their fractional data team. We advise on, build, and manage data platforms. Our strategy, proven with over 300 companies to-date, expands multiples through data transformation, as presented in our book, The Dashboard Effect.

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Caleb Ochs:

This is The Dashboard Effect podcast. I'm Caleb Ochs, and I'm here with Kate Eberle, and today we're going to talk a little bit about some manufacturing KPIs and some of the stories that we've seen over the past few years. Hey Kate.

Kate Eberle:

Hey Caleb.

Caleb Ochs:

So today with the manufacturing metrics and stuff that we're going to talk about, why would people care?

Kate Eberle:

Yeah, I think in manufacturing in particular, I think metrics are pretty core to that space. You think about Lean Six, Sigma, Toyota coming in however many decades ago, and it just seems like manufacturing and metrics are a match made in heaven. But one of the things we also hear a lot from clients is,"Well, what are other people doing? What are we not taking into account that you in that seat, having worked with so many people, can share with us?" So I think we're gonna hit on some of the common stuff, and then maybe touch on some of the use cases that maybe aren't so common, and just kind of dig in.

Caleb Ochs:

We do hear that a lot. People asking, "We think this is what we want to report on, but what are other people doing? Can you help? Can you enlighten us on that a little bit?" And we do to some extent, but I think this is gonna be a good episode to show some of the things that we see. Some obvious things, some maybe not so obvious things, and hopefully that will be helpful to somebody.

Kate Eberle:

Yeah, for sure.

Caleb Ochs:

Alright, so how do you think about manufacturing high level?

Kate Eberle:

So, just boiling it down, it's all about producing goods. So taking a bunch of raw materials, transforming that into something that's value add, and then getting that out to your customers?

Caleb Ochs:

I really like boiling things down. Obviously, manufacturing is a complicated business, but you described it in simple terms, and that's sometimes the best place to start. You know, the three questions that we were talking about before this were, "Do we have enough demand? Are we outsourced? How's our sales going? Do we have enough cash to keep buying things and producing other things?" And then, "Are we delivering what we promised when we promised it?" Right? So I think that, at least for this discussion, we'll stick to those three buckets, and talk about some of the metrics that we've seen in there, and maybe some stories about some of the things that we've seen as well. So, let's start with that first one,"Do we have enough demand?" Some of the things that come to mind for me, and some things that I've seen doing this for a long time, is just looking at what you're quoting. What are the size of the quotes? How long is it taking you to get the quotes out? Are you doing as many quotes as you would target to get out there? I think I was just looking at a report before this where we had a chart, and it's fairly simple report, but there was a chart around the sizes of the quotes, and they just bucketed them into small, medium, large, extra large quotes. And you could just see how that would be helpful to say, "Oh, we're doing a lot of small quotes. Is that good? Is that what we want?"

Kate Eberle:

Yeah, so you kind of described what's happening at the highest level. So, we have a budget for the year, we need a certain number of quotes to hit that budget, how is our actual performance and then seeing that actual forecast, giving you a bit more of a leading view on where performance is going. I think the next nice area is actually down to the rep level. So giving your sales operations team the visibility they need to actually execute against those budgets. We're seeing this more and more on the sales front, just getting that visibility into the sales manager view so they can see how all of their individual reps are performing against their goal, allowing them to say, either, "Across the board we're seeing a trend on a particular maybe SKU or product category." Or alternatively,"Man, this rep is just not pulling their weight, I need to take some more time to coach with them to try and get their numbers up." So we're hitting at the aggregate level, so I think that's just another great area for sales reporting to come in, particularly for manufacturing.

Caleb Ochs:

Yeah, and what I like about that is that it's different than what you would typically think of in manufacturing reporting. It's more of a business reporting. But when you're talking manufacturing, KPIs and stuff, a lot of times it's machine downtime and throughput and utilization, those types of things, but it's important not to overlook just the basics of, are you selling enough?

Kate Eberle:

Yeah, well, I think it's a nice segue into the next area, that financial piece, "Do we have enough cash on hand?" Obviously the past few weeks cash is top of mind with a lot of folks were talking to. But I think really just from that financial perspective, do you have a clear view on your AR/AP? And do you know what you expect to be coming in the door versus what's going to be going out the door? Can you see that visibility out into the future? That's another good space where you don't need to have to wait to see what invoices are hitting, you could be able to predict that and get a bit more of a leading view on the organization. I think the other piece that also comes in from a financial perspective is just managing your inventory. Do we know what we have on hand? Is that going to be sufficient to fulfill the orders that we have? You definitely see that start to bleed into the financial space as well.

Caleb Ochs:

Yeah, those things are very important. So I used to be an inventory analyst, a long time ago. But a huge part of what I reported on was, "Here's what we have on hand," and the sales reps used that information to be able to, first of all, promise delivery dates and stuff, because if we didn't have it, obviously, we'd have to make it. And then, just knowing what our liability was at a high level. We were a huge company, so it was very important to know what our inventory levels were. We had, 10s of locations where we stored product across the country. So, super important to make sure that inventory is turning into cash so you can keep your lines of credit going.

Kate Eberle:

Yeah, I think you raised another good point. I was just talking to a client a couple of weeks ago whose sales reps had no single source for what their inventory looked like. So oftentimes if reps are moving fast trying to move product out, it's conflicting reports of what's available. So you have those cases where there's tension across the sales team, they're not able to operate as one unit, and then you're getting different messages that you're sending to the end client about what's available and what you can actually deliver.

Caleb Ochs:

Yeah, super important. So the last thing, the last topic. We just touched on, "Do we have enough cash?" The last one is, "Are we delivering what we promised when we promised?" This is a little bit more standard manufacturing KPI area, but what are some of the things that come to mind there?

Kate Eberle:

Yeah, I think just starting with the basics, throughput. How long does it take us to get something and transform it from raw materials into the product that we sell? I think that total duration you just see really boil into Lean Six, Sigma, control charts, are you tracking your defects over time, and actually actively managing your quality. So I think a lot of those metrics are pretty commonplace, and then naturally just transition into process efficiency. "Are our machines operating as effectively as they could? Are we actually able to diagnose pretty quickly when something is down where the challenge is coming in the production process?" And then labor as well. "Are we adequately staffed to manage the machines and the production process? How long does it take to hire if we aren't?" I've worked with some clients recently who've had plants in areas that are, I think, more rural Missouri, so they've just had a heck of a time actually getting the people that they needed to operate the plants. So that takes better visibility into hiring and the HR side of the house. So everything from what you need to know about machines to what you need to know about the people who operate them. I think we've touched on a number of areas that we've seen metrics work in manufacturing, and hitting those three questions I think is a great place to just situate your particular company in the spectrum of where you might start a BI effort like this. But do you have any thoughts, Caleb, on how a company might get going in any one of these areas?

Caleb Ochs:

Yeah, so I was just reading a short case study, it was like three pages, on Harley Davidson,and what they did in some of their manufacturing, in some of their data initiatives. And essentially what they're trying to do is become more efficient, right. And all have their machines didn't have sensors and stuff on it, so essentially the predicament they found themselves in was, "We don't have all the data that we would want." But they found a company that came in and built some predictive AI and stuff on the data they did have to try and predict in other areas where they might have downtime, and they were able to do that. And with like a month of data they were able to figure out with like a 90% certainty when machines were going to be down, and that saved them like 10% in their their downtime. Now, the key takeaway there for me is not, "Let's all go do AI," because I don't think it necessarily applies everywhere, and Harley Davidsons huge. They've got a lot of data to work with and that's possible there. But I do think the key thing is, focus on the data that you have. It's tempting to want everything to be perfect and to want to, for example, get all of your plants into a single pane of glass. Sometimes just starting with 50% is better than having 20% here, and 20% there, and 10% here. Start with 50%, and then work your way through it. But focusing on what you can do now can also pay big dividends. A lot of the companies we work with are buying other companies, and they've kind of built up a company through acquisition. So they've got disparate locations, right. We had a client not too long ago that was dealing with something like that, and we built some reports for them and I think you were a lot closer to that than I was, but can you tell us about that a little bit?

Kate Eberle:

Well I think, describing what you typically find in a warehouse, that focus already on metrics, it's often just really manual. So you get to the warehouse floor, they'll probably have some sort of whiteboard showing you their throughput, showing process, adherence and safety metrics. The challenge is, while that may work really well for one factory, if you're sitting in the executive suite, trying to manage an entire organization that now has multiple factories or warehouses, you're just not going to get that real time visibility to figure out, "how do we move this entire ship forward," versus an individual physical location. So I think the really nice use case working with this company was taking what were multiple ERPs, and actually automating some of that tracking they were doing on the shop floor to then give them a more holistic view across factories. Also figuring out how they can actually optimize load distribution. If one factory was actually booked to capacity but another factory wasn't, how could they manage that demand more effectively so that they were capturing their existing capacity. And they also actually had a nice component of their business where they could get quick turn more premium pricing, getting better visibility into how they could really leverage that maximize their margins and just really operate seamlessly across various different locations.

Caleb Ochs:

Yeah, I remember that they had that ability where that quick turn was their most profitable project. And with that visibility to see, "Can we take this, and quickly?" It's all about quick turn, right? So,"Yes, we can take it at this plant," when before they didn't have that visibility. It's huge. Very, very beneficial for them. And we see that a lot. It's crazy how many manufacturers have grown that way, and then they find themselves in this predicament of, "We have data at all these locations, and it's just siloed there. How do we pull it all together?" It's a daunting task, because it is no small task. But there's techniques and stuff that you can use to get there. And it is kind of where we've lived for a long time, and you can see how beneficial it is to actually do that exercise and get some of that global reporting done.

Kate Eberle:

Yeah, it's definitely been pretty transformative for the manufacturing clients we've worked with. I think there's a great webinar, Elgin Fasteners. I definitely recommend checking it out if you haven't. But really, you can see that effect on productivity, and I think that's the beauty of manufacturing.

Caleb Ochs:

Yeah. All right. Cool. Well, hopefully what we talked about was was useful. I think, at the end of the day, every company is gonna be different, and you really do need to look at what you're trying to achieve and how you might be able to do that. But it's helpful to know what else is out there and maybe some of the things that you're not quite thinking about.

Kate Eberle:

Yeah, completely agree.

Caleb Ochs:

All right. Cool. Well, thanks, Kate.

Kate Eberle:

Thanks Caleb.