I had a different blog ready to post that dealt with Performance Reviews, but considering recent events, I instead reflected on the situation we’re currently facing as a society. Simply put, we are in uncharted waters, a global pandemic.

Each of us is managing through the uncertainty that arrives with every COVID-19 newscast, social post, conversation, and email – both personally and professionally. We need something to anchor against. I’m a big process guy and I always like to beat up my processes so to see if they can hold up against any circumstances I can think of. I didn’t think of this one, but now we’re here, so let’s beat it up!

I’ve spent most of my career managing Sales & Operations Planning (S&OP) and Integrated Business Planning (IBP). For those of you not familiar with these areas it is a way to create demand plans and ensure they align with the supply plans. Do it right and you will improve inventory performance, delivery performance, and cost. In addition, you will have consistency and clarity across all operational segments leading to a more productive and happier workforce (think efficiency and retention). Done wrong, or not at all, and you have chaos. Like an orchestra that’s never played together type chaos. They’ll get through the show but it’s going to be messy, the audience won’t like it (they might not come back), and the players won’t be too happy either (employee engagement).

Pre-Crisis

Let’s go back to before the crisis and establish S&OP and IBP theory. You first need a demand plan or Operational forecast. If you don’t have one, see my earlier blog on Simple Forecasting. This is pretty critical. An Operational Forecast is the company’s best estimate on what they believe they are going to sell at a unit level. This then drives through the MRP system to generate purchase requisitions and planned production orders which are the supplies needed to satisfy the demands. This forecast will also be used to determine capacity needs both for your factories as well as your suppliers. Being armed with this information helps these supply areas plan better which improves their efficiencies and inventory performance.

Before you put the Operational forecast into the MRP system, you need to validate it against the Financial and Sales forecasts. Financial and Sales forecasts are what the executive team has committed to their higher-ups. And there’s always a “higher-up” whether it is a board of directors or Wall Street. Through a series of consensus meetings, you need to understand if the Operational forecast is lower or higher than the Financial and/or Sales forecast and get it in line.

If the Operational forecast (again, what we’re driving in our MRP system) is LOWER than the Financial and/or Sales forecast, you risk not hitting your financial or sales plan. Or, in order to hit that plan you will likely incur additional costs associated with overtime and expediting. If your Operational forecast is HIGHER than your Financial and/or Sales forecast you risk bringing in excess inventory which eats up cash, warehouse space, and could eventually become scrap.

The Crisis is Here

So why do I bring this up? Well, a global crisis is upon us and it appears we’re headed for a recession. If that statement becomes a reality, then our forecasts need to adjust due to market forces that have changed significantly. Across functions, we need to understand exactly what market force changes will happen and where they will take place, meaning, which product lines might be impacted.

Look at Your Forecast

At an aggregate level, if Finance and Sales believe we are going to be down 20%, then we must make sure our Operational forecasts reflect this drop. After our forecasts are adjusted, we can alert our supply areas such as factories and vendors of the drop in demand. They can then make adjustments in their supply chains.

But what if we don’t change the forecast? If we don’t reduce our operational forecasts and the market does indeed turn downward, we’re headed for excess inventory and excess capacity which are very operationally inefficient.

By the way, the opposite holds true if you’re in an industry that is seeing an increase in demand such as face masks, rubber gloves, cleaning supplies, and toilet paper. You will want to increase your forecast to the appropriate amount and see how that impacts your factories and suppliers.

So, does the process work? Yes, it works. A well-defined S&OP or IBP process is logical and everyone is on the same page. This is a continuous process that needs to be done and re-done several times per year. But by doing so, we can avoid some unnecessary costs and headaches associated with these dramatic changes.

Moving Forward

So, I don’t know for sure what the future holds, but with an IBP process that is integrated across functions, you can be better prepared for it.

Early in my career, I was tasked with outsourcing a product we were producing at an internal factory. Leadership expected to realize a number of benefits by outsourcing the product including opening up capacity in a constrained plant, achieving product cost savings through economies of scale, reducing inventory dollar and space burden, and reducing customer lead time. The first three benefits – capacity, cost savings, and inventory reduction – were tangible and quantifiable. But, the benefit of reducing lead time was going to be more difficult to quantify.

Predictability Does Not Equate to Forecasting
To achieve economies of scale, shrink inventory and reduce lead times, we developed an agreement with the vendor, giving them blanket orders. There are many advantages to this type of agreement that I’ll go into in another blog. This particular product that I was involved with was considered a commodity in the market, and demand was fairly predictable. (My apologies to any product managers reading this who despise products being referred to as commodities.) Predictable situations still require an effective forecasting process. Fortunately, we already had an effective and powerful forecasting process in place, so my job as a sourcing person was instantly that much easier.

Establishing a Process
Critical language in the vendor agreement included orders that were placed with the vendor by noon would be delivered within 30 hours. For example, if I placed a PO with the vendor by noon today, they would deliver it tomorrow by end-of-day. Giving myself a bit of an insurance policy, I set the available-to-promise (ATP) lead time in SAP to two days. So, let’s say it’s Wednesday and a customer order comes in today and there is no inventory on hand, we would promise to ship on Friday. After completing the vendor verification process, and ensuring they could produce the product to our quality standards, we were off to the races. Cool, process established.

When Operations Positively Impacts Sales Numbers
At the time of sourcing and forecasting this product line, I had a sort of hybrid-job. After the first month, I noticed sales were increasing on this particular product, exceeding my expectations. But, one month a trend does not make so I noted the anomaly and checked it again the second month. Sales increased again. And again the third month. After the third month, I spoke with the product manager to understand if something in the market had changed that resulted in an increase in demand. None of the other products in this line were increasing at the same rate (or at all for that matter). He said that nothing had changed, this was an old product and he had no idea from a market perspective why this would have changed.

I then called someone in the customer service/order entry group to see if they had any insight. What they told me was a real eye-opener. She said that when we were producing the product in-house, lead times were set at 30 days. A customer would call and ask if we had the product. If it wasn’t on hand, they would get the lead time, 30 days. Unfortunately, a significant percentage of the time, the customer would hang up and call a competitor (again, this was a commodity product) and purchase it from the competitor. We didn’t even know we had “lost” the sale. But after we reduced the lead time from 30 days to 2 days, the customer was willing to wait the 2 days and placed the order with us. Sales on this product went up ~30% and maintained that level. So now our lead time reduction had a tangible benefit, increased revenue! Who would have guessed? Couple the increased revenue with the increased margin from the sourcing activity and the inventory reduction saving us space and working capital, we had a win/win/win/win!

Superior Service & Identifying Trends Are Key
In today’s world of Amazon and other e-tailers delivering the product the same day or next day, this solution may be more obvious (or maybe it isn’t). At the time it wasn’t obvious. Today in a B2B world, we can learn a lot from these companies in providing better service to our customers. Don’t give customers any reason to call someone else! And if one of our competitors can’t deliver, then we have a process in place where we can and we gain market share. In this case, it was really just an investment of sourcing time and process development.

So there you have it, those operations guys can help the company improve sales!

If you’ve spent any length of time in purchasing you’ve probably come across the “QBR” or Quarterly Business Review. This is a well-intentioned meeting between you and your suppliers that occurs…well quarterly to review their delivery and quality performance. Many times specifics aren’t discussed and expectations aren’t clear and neither are the action items. You then part ways until the next quarter where the cycle continues. Everyone has done their job “playing work”.

I’m a big accountability guy. I measure things; a lot of things. If there is a measurement that is going to help keep a process in control, I’m on it. Measurements need to be accurate and timely.

From a purchasing perspective, vendor scorecards are great. It gives both sides an opportunity to level-set on performance versus expectations, discuss any open issues from the last meeting and actions that are going to help improve performance. Instead of quarterly, vendor scorecards should be reviewed monthly.

Identifying Suppliers

The first step is determining which suppliers you’re going to do scorecards with. These are called your “key” suppliers. Which vendor you include in the scorecard process could be based on size (i.e. how much of your spend they represent), importance to the business (i.e. only supplier in the world who can make critical parts for you) or risk (i.e. a supplier that is struggling and is key to your success).

Next, you need to set clear expectations for performance. The mainstays of criteria are quality and delivery performance. More advanced supply chains will include safety and cost criteria.

Setting Expectations

Let’s start with quality because frankly, nothing else matters if the quality is crap. Getting a bad part on time at a low cost is of very little use to you. I’ve always measured vendors on a DPPM (defective parts per million) scale. The calculation is simple: number of defective pieces detected in a month divided by the number of pieces received in that month times 1,000,000. Let’s say you detect 150 defective pieces in a given month. You received 10,000 pieces from that supplier that month. You take your 150 / 10,000 = 0.015 x 1,000,000 = 15,000 DPPM. Is that good or bad? You need to decide what your company is willing to tolerate. As a starting point, I’ve always said that anything over 5,000 is concerning and needs to have prioritized improvement activities for the vendor. Anything less than that is relatively decent but I would like to see actions toward improvement over time.

Next, we have delivery performance. At a bare minimum, you should measure your suppliers against their promise date. You can also measure their performance to your request date but we first need to make sure they can live up to their own promises. As an example, let’s say you place an order requesting delivery for October 10. They confirm the PO for a delivery of October 20. If they deliver the PO on or before (no more than 3 days early) October 20, they’re considered “on time”. Anything after that, they’re late. So the calculation is pieces received late-to-promise date divided by the total number of pieces received that month. If 500 pieces were received late out of the 10,000 total pieces received. That would be 500 / 10,000 = 5.0% late, or 1 minus that number for 95% on time. So, which is it, 5% late or 95% on time? Keep reading.

I used to look at suppliers’ “on time” number which is nice but not as useful for problem-solving and continuous improvement. I prefer to look at their “late” number because it gives me direct access to the number of “problems” that need to be solved. Let’s go a step further on that topic.

The supplier delivered 500 out of 10,000 pieces late. The expectation for problem-solving becomes more clear and would entail taking the 500 pieces and assigning reason codes defining why they were late. The vendor should do this activity and present their findings to you in a Pareto chart in descending order. That may look like this:

Reasons for 500 late pieces:

• Labor capacity: 300
• Machine down: 100
• Lost order: 50
• Late arrival of raw material from the vendor’s vendor: 40
• Inventory inaccuracy: 10

Taking Action

Once they’ve identified the reason codes, they need to decide what actions are going to be taken, by whom and by when to solve the issue. I’ve found it is more effective for the supplier to solve one issue at a time. Stay focused, be accountable. If they come back to me and say, “We’re going to solve the inventory accuracy issue by doing a full physical inventory of our plant.” That’s great and all, but that only represented 10 pieces out of 10,000 or 0.1% of the late pieces. Instead, I want to hear about the specific actions related to the Labor Capacity issue which is 3.0% of the total misses. Actions for this could be hiring additional labor, using a temporary workforce, adding overtime, or improving efficiency in specific areas (or a combination of those). Then, I want to know who is doing it, by when and what kind of impact it is going to have. We will note that as an action and everyone will go on their way until next month.

Validate Action Implementation

Once the supplier implements the action, we measure again to see if their actions were effective and if so, they should move on to solving the next problem. In an ideal world, they keep solving problems and we reward them with more business. An added benefit of this for the supplier is these improvement activities will help them not only improve performance for us as a customer but for their customer base as a whole. This should result in additional business to help their company grow.

Supplier scorecards aren’t meant to “punish” suppliers for performance when they don’t meet agreed-upon expectations. They are meant to set clear expectations and help suppliers focus on the issues that make the business relationship more productive which is a win/win for both sides.

Raise your hand if you love meetings!

No?

No one?

In today’s corporate environment, there are A LOT of meetings: some useful, some not so much. Whenever I’ve been in charge of a factory or department, there is one critical meeting that helps determine the success of the day (which feeds into the success of the week, the month, the quarter and the year). The Daily Morning Meeting. This meeting serves as a forum for department heads to discuss and understand what is going on in their group and status their peers, superiors, and subordinates. The Daily Morning Meeting sets the team up to be successful, and the company can attain its goals from a safety, quality, delivery, and cost perspective.

Each department report-out in the Daily Morning Meeting has three parts: yesterday’s plan, yesterday’s actuals, and today’s plan.

Let’s walk through a scenario, using a parcel shipping area as an example. I first want to understand yesterday.

Yesterday’s Plan

The department head needs to explain what their plan was. I’m a numbers guy. When I ask how you did yesterday, “Good” by itself is never an acceptable answer. I need numbers. So in the parcel shipping area, let’s say your plan yesterday was to ship 2,000 packages using 10 people in 8 hours. Achieving that objective would give you an efficiency of 25 packages per hour per person (2,000 packages ÷ 10 people ÷ 8 hours). Anything more than that is excellent, and I want to know why. Anything less than that is not good, and I want to know why.

Yesterday’s Actuals

Second, I want to know how the department adhered to the plan. Let’s say, using the plan above, the supervisor says, “We shipped 1,900 packages with 9.5 people in 8 hours, so our efficiency was 25 packages per hour per person (1900 ÷ 9.5 ÷ 8).” Let’s break that down. Your actual number of packages shipped was lower than expected. That might be okay as long as you didn’t leave anything past due. But we need to understand why we were under plan for volume.

Additionally, you had 9.5 people on a plan of 10. Where did the other operator go? Did an operator go home sick? Were they farmed out to another area for half a day? Either way, I would view these numbers to be acceptable from an efficiency standpoint, and the process appears to be in control.

But what if they only shipped 1,500 packages (on a plan of 2,000) with 9.5 people in the 8 hours? That would be an efficiency of 19.7 packages per hour per person (1500 ÷ 9.5 people ÷ 8 hours) on a plan of 25. Not good. I’d need an explanation. If you didn’t leave any past due and the volume was just lighter than anticipated, you should have farmed out people to other areas or had the operators focus on 5S activities. If you did leave past due, something went really wrong. Your delivery and cost performance were substandard. Simple hour-by-hour boards should have told you that you were going too slow and getting behind the plan. Leads and supervisors have an obligation to assess the situation throughout a work day and make adjustments.

On the opposite end, if you actually shipped 2,400 packages with 9.5 people in 8 hours, then your efficiency would have been 31.6 packages per hour per person. Wow! You need to understand why you kicked so much tail (make sure it wasn’t a goofy anomaly) and celebrate with your team. Let them know they hammered it yesterday and brag to your peers about how well the team. Raise the bar! People want and need recognition for a job well done!

Today’s Plan

So you’ve reported yesterday’s plan and actuals. Now you need to talk about what you’re going to do today: today’s plan. Again, numbers are required. The department leader would say, “We have 2,300 packages to ship today, and I have 10 people. Our average efficiency is 20 packages per person per hour, so I only have the capacity to ship 1,600 packages (2300 ÷ 10 people ÷ 8 hours).” Whoa, we are short! How short? The supervisor should come prepared to the meeting – calculations complete – and say “I’ve got 2,300 packages planned minus the 1,600 I have capacity for which leaves 700 packages on the table. 700 packages ÷ 20 packages per hour per person ÷ 8 hours per person, so I’m 4.4 people short.”

That issue needs to be solved before you leave the meeting!

Solving for Today’s Plan

A short-term labor shortage can typically be solved in one of three ways (in this order):

First option: are there any extra people in the factory that can be reallocated toward this area? Redeploying resources doesn’t require overtime and gives people new skills.

Second option: can I apply overtime? Not great, but at least we keep up our delivery performance and customer satisfaction stays in check.

Third option: can I move out any orders or let them go past due? This is the worst option, but it is planful, and we are communicating our issues versus randomly disappointing customers. In my experience, customers are pretty understanding as long as you communicate with them as proactively as possible. Once today’s plan is solved, we move onto the next department for their report out.

The Daily Morning Meeting is important. We aren’t leaving our operations to chance and hope. We are articulating a clear plan to achieve success for the day.

Keep it simple

A note on the numbers: these should be simple and clear. Everyone in the room should be able to understand them from the plant manager to the department leaders to HR. Everyone should be able to read the numbers, do some quick math and understand the situation. Too complex of calculations and you will lose people, and then your team doesn’t know if things are good or bad.

This type of meeting can take place in any operational department. I’ve led these meetings in purchasing, forecasting, material handling, production, and distribution. The meetings provide clarity and shows leadership your area is under control. Once expectations are established and you’re in a meeting cadence, you and the team will look forward to this meeting and become energized about the day!

When I was attending the University of St. Thomas, one of the majors I pursued for a period of time was Finance. Then came the “Finance II Project”. This was some sort of financial analysis project of a public company. I remember two things about this project: my subject company was Kimberly Clark and I got so lost in the “forecasting” section it wasn’t even funny. I finished the project, received some marginal grade and promptly switched my major to Operations Management (Supply Chain) where things made sense.

Shortly after changing majors, I landed my first internship at ADC Telecommunications. I knew I was incredibly fortunate to work for this company as they were as close to APICS for operations as you could get. I also had some great mentors in the supply chain area, specifically in forecasting. [Note to interns and grads, find a solid mentor or two who you can use as a sounding board.] I was still a little tender from my Kimberly Clark project but I had to figure out what Supply Chain Forecasting was all about.

Let the Learning Begin!

I sat down with my forecasting mentor (who I hope is reading this and bless his patience) and he white-boarded (for I don’t know how long) trying to help me understand supply chain forecasting concepts. At the time, we were using SAP’s standard forecasting module and it had a plethora of fancy forecast algorithms you could use depending on your situation. In reality, forecasting month after month and changing models that I didn’t really understand in the first place didn’t give me a ton of confidence in the forecasts I was generating. Then if a number didn’t align, it was difficult to figure out what caused the numerical hiccup, let alone explain to the stakeholders what I was thinking.

Why Forecast?

But let’s hit ‘pause’ for a moment. Why do we forecast at all? Very simply put, we forecast because the time (lead time) it takes to produce our product is longer than our customers’ willingness to wait. If we don’t have product available in a reasonable amount of time, customers will go somewhere else. Think of it like this, if you go to Home Depot to buy a shovel and they tell you it will take 12 weeks to get it, you’re not going to wait, you’re going to Menards.

A Simple and Effective Model

Fast forward several years; I’ve left ADC and I’m at a different company, managing the forecasting group. We came up with a very simple, yet extremely effective model. It had three inputs: average historical sales over some period of time, a trend profile and a seasonality profile.

So how do we create a simple forecast? Let’s start with our old friend the “average.” This is one of the most basic forecasting models you can use. Pick a historical time horizon: 12-, 18-, 24- or 36-months back. In the organizations I’ve been with going beyond 2 years doesn’t give you any better data so 24 months is as far back as I will go. Averages by themselves can be a “good enough” forecast. But we can make them better in businesses that have seasonality, which many do.

After you’ve established the historical timeline, you need to add your trend profile. This sounds fancy, but it isn’t. A trend profile is useful in a company or product line that is growing or shrinking at more than ~5% per year. It is used to project the product’s upward, downward or flatward (not a word, I know) trend. The easiest way to calculate a trend profile is to do a straight year-over-year comparison. Let’s say we sold 1,500 units last year. You simply compare it to the previous year’s sales of 1,000 units and come up with a 50% increase. If you expect that trend to continue, you would add 50% to last year’s total coming up with 1500 x 1.5 = 2,250 units for the next 12 months. See? Forecasting is easy!

The final step is applying the seasonality profile. Just the term, “seasonality profile” sounds complicated. It is far from. A seasonal profile is just calculating the proportion of a particular month compared to the entire year – again, using historical data. Using the same numbers from the previous example, let’s say you sold 1,500 units in the last 12 months and specifically 150 units in January. January would have a seasonal factor of 150/1500 or 10%. If you sold 300 in February, February’s seasonal factor would be 300/1500 or 20%. If you sold 263 units in March, March’s seasonal profile would be 263/1500 or 17.5%. One note of caution: doing a seasonal profile at the material level may give you results that jump around more than you want. I would suggest to put your seasonal profiles at a higher level, like material group or product line and then “disaggregate” that forecast down to the material level. That’s another blog for another day.

An Example

So let’s put all of those concepts, averages, trends and seasonal profiles together and do a simple forecast. Based on the average of the last two years you sold 1,500 units per year. That’s your average. Your YOY growth was 50% so you believe you’re going to sell a total of 2250 units in the next 12 months (1500 x 1.5). You now apply your seasonal profiles and your forecasts going forward are calculated as:

• January: 2250 x 10%: 225
• February: 2250 x 20%: 450
• March: 2250 x 17.5% = 394

That’s it, you’ve created a very nice baseline forecast!

You’re using facts (last year’s performance) to project the future. If the trends and seasonality continue, you will have the materials in place for your customers. Customers will be happy and they will return to you to buy more products. Customers buy more products and your company grows. Your company grows and hopefully everyone gets a raise and a nice bonus.

Again, this example outlines a baseline. There are other factors such as projects (one-time big deals) that can influence these numbers and you can just add those on accordingly.

Happy Forecasting

I hope this has given you a little more confidence and/or understanding to calculating forecasts. I promise this is just as effective as using a fancy model that comes with an expensive ERP add on. The advantage? You know how this is calculated and you can explain it at any level in your organization.