During this 30-minute webinar, which will include a demo of the solution, Lanham Associates will provide you with a basic overview of their Demand Planning system, focusing on how its functionality can help optimise your inventory in these challenging times.
Introduction to Demand Planning and Lanham Associates
We are Lanham Associates, and I’m going to be talking about demand planning that runs inside of Business Central.
What I do is demand planning for Lanham Associates and that’s all I do.
All right, so demand planning runs inside of Microsoft Business Central. We’re an Independent Software Vendor and Demand Planning looks and feels just like Business Central.
You really can’t tell where one ends and Lanhams begins because it looks so similar.
So, when we talk about forecasting, I want to talk about, you know, that our mindset is how we how we at Lanham Associates look at forecasting.
Really, two parts of the forecast is the part that’s based on history, and for that, we use, the power and the strength of a computer. That is how our system is designed. On the other side of the equation, you have factors outside of history, and we use the power and the capabilities of people. So, we designed the system, so that people can do what they do best.
Look at history, really history speaks to us when we go through our processing, we find that there’s a pattern.
That history tells us that this item is forecasting this way, and you’ll see what I mean in a few minutes. That activity, as it turns out, is most of the forecast items that you have.
For most businesses, we use something called best fit formula calculation, which, which I’ll describe a little bit. So, you’ll understand what we mean by that.
On the other side of the equation, there are factors outside of history: market knowledge, those things that are going on in the marketplace where really can’t look at history to know what will happen in the future.
This turns out to be a few of the forecast items and they’re about new items, new markets, new customers, so anything that’s, that hasn’t happened in the past, where people, market actors are going on, people who have the knowledge, and can have input as to what the forecast is on those, and you would not look to history to tell you what will happen in the future in that regard.
So, um, when we talk about history, we want it to be good. So, you know, you think, well, all my history is good. Well, you probably have some items that are that are going away.
And you’re not going to sell those anymore. So that history, you don’t want to use to forecast the item that’s going away, but you may have an item that replaces it. So, you want to redirect the usage for the old to the new.
Or you may have a brand-new item that’s alot like an existing item, but doesn’t replace an item.
And for that, you might want to clone usage. So, we give you the ability to redirect and clone usage.
We also give them the ability to say, well, I need to exclude this sales order as it won’t happen again, it’s not representative of what we expect to happen in the future.
Or maybe you want to exclude drop ships.
If you’re shipping directly from your vendor to a customer, you can exclude drop ships or you may want to smooth usage.
We have given you the ability to say, well, if something, the current month is less than 20% of the average of the past 12 months or more than 200% of the average of the past 12 months, I want to smooth the usage. So, we give you many, many ways. These are just some of them to make history representative of what you can expect to happen in the future?
So, I want to talk about best fit formula selection because that’s how we do our forecasting.
So, if we think of an item, you’d like to have 24 months of usage, right, 24 months of history that we can look at. In this example, we’re looking at one item we know what we sold for the past two years, we can we can look to see last month what did we sell and can it be forecasted. So, we might take a simple formula that says, I’m going to look at six months going LP2 to LP7, those 6 months and forecast what happened last month.
Then compare that to the actual calculated percentage and we do it again. We step back a month. We do it again, we step back for another month. We do it three times.
You decide how many times you want the system to test a formula, because each time it comes up with an error percentage, we’re going to look at all those error percentages and then do the logical thing.
Let’s use the median error of those tests that we did for Formula 1. Then we go and say, all right, we’re going to take another one.
This time it has eight periods. We’re going to forecast once, twice, three times, come up with three different forecasts, compare to each of the actuals, come up with a forecast error for each, and then take the median error percentage.
The system demand planning view comes with 18 formulas. You can add additional formulas but it comes with 18 formulas and we’re going to test each one of those formulas calculate the median error percentage and then do the logical thing.
We’re going to take that formula with the lowest error percentage error and we’re going to use it. That’s the formula we use for that item until history changes, which is at least at the end of a month.
It may happen that for some other reason, you may adjust history, or that may be some factor that changes history, but any time history changes, we’re going to go through this best-fit formula selection.
So that’s how our best fit formula works in just a high-level view.
We also do some things to give you the ability to collaborate with customers.
So, we’re going to do the same kind of thing where we take they some items that you identified for a certain customer, maybe not all customers and say, I’m going to take the history for those items I pick, go through that same formula selection that will come up with a forecast, the working collaborative forecast, share it with either the customer or sales savvy person.
Now, tell that customer three things, here’s what we come up with for our forecast.
Secondly, here’s the history of what you bought same month last year.
And lastly, most importantly, here’s that forecast number that you gave me last month.
We have one question: do you want to change it? After the customer reviews that and makes their adjustments it comes back as a spreadsheet, and we import it back into the system. So, those same items may also be sold to other customers. We’re still going to forecast those with their usage, combine it with this collaborative customers forecast.
Q: Someone has a question: you mentioned about historical forecast from the last 24 months, this is specifically from a wine client, what happens if it’s a new vintage and you don’t have all of that historical data. How would it work then and can the system handle that?
A: Yeah, sure. So, as I just said a minute ago, we could clone usage if it’s a lot like an existing item.
We’ll give you a number of different ways, and I’m just going to go through just few of them. You give them the ability to set up a promotion. So, you can say that promotion is really a way to adjust the forecast.
And you can put in some numbers and say, this is what I think the forecast is, because if you have a brand-new item, now you’re probably have a plan for what you expect to sell, and that’s a good place to start until you have some history.
So that’s the part where we give people their opportunity to use what they know, to input it into the system. If all you know is history, then it’s better to use the history.
So hopefully that’s a little bit of clarity on that.
OK, so, moving right along. This is a high-level look at our system. We really got two engines: forecasting engine and a replenishment engine. I talked about getting good history.
The system runs through those 18 formulas, plus any that you may have added.
It’s going to find the best fit formula, it’s going to use that. You can also take some items and do a collaborative with your customer.
You have that ability just talked about promotions. You can, you could have a true promotion, right?
And you could send promotion quantities in, give you the ability to also after the promotion is over if you so choose to have that history removed.
Will the idea that this is a one-time event you decide. So, we give you the ability to do things, to add things to the forecast future sales promotions. We also give you the ability to summarise the forecasts. Because, yes, you may look at individual items and it makes sense. But what does it add up to, so we could give you the ability to add it up, not just in the unit cost of goods sold. So, you can see it in dollars.
I’d say hey, does this look like what we spend on an annual basis either looking backwards, looking forward and if it doesn’t, then you can drill down and find those items where something is happening different than what you expect.
And, of course, you can make an adjustment, whether it be the usage for an item, or you can make just a forecast adjustment.
We bring it over the forecast over to the replenishment side for those things that are kits, we’re going to forecast the end item, and then we’re going to use your bill of material in your minimum multiples, call for quantities, what we call forecasted assembly quantities, or forecasted production quantities.
We’re going to explode those quantities to call for the components of those things that you just buy and sell.
We’re bringing over a forecast, and we’re going to look at the expected Inventory in the future and say: well, do I have enough to last?
And that expected inventory is at a specific point, what we call it a lead time horizon, so we look at the lead time plus the vendor review cycle, how often do I want to review this vendor?
If we see the inventory negative, we’re going to give you a suggested order. We also identify a surplus. So, if you’re getting a suggestion to buy something that you have surplus somewhere else, you’re presented with, you have surplus at another warehouse, and you can choose to bring that in, and use that inventory instead of buying more. We also give you suggested transfer.
So, if you’re doing public spoke, where you have inventory in one where I have some main warehouse feeding other warehouses, we’re going to give you the ability to transfer, inventory, over using a suggested transfer, which I’ll talk about a little bit in a few minutes.
On the Replenishment side. We replan frequently, we’re going to roll up the usage, so when we’re planning at the hub, at your central warehouse we’re going to look at the anything you’ve sold at any of the spokes, add that to come up with the forecast, inclusive of everything, so that you make sure you replenish it whether that’s assembly, production or purchase to your main hub. So, you have inventory for all of your spokes that you feed.
We’re also going to, as I said, we’re going to calculate dependent demand for those component items and we’re going to help you a whole lot by reducing the time you spend doing all of these calculations.
Usually we go into a situation where, without this kind of system, people are spending a lot of time doing things with spreadsheets and they’re scratching their head. And then the headache and spending all this time. And it’s, you know, maybe 80% of your time is spending, preparing to make a decision.
And then maybe 20% you’re actually making a decision.
Once you have demand planning, you are now in a position where the information is sent and you make a decision about what it is you want to buy and assemble and purchase.
So, on the replenishment side, when we’re looking at Hub and spoke, these are, this is a diagram of hubs and spokes. These are Warehouse 1, 2, and three would be a hub.
So, would be warehouse five, we’re going to roll up all of what we sold at the hub and use that usage to forecast. So, we have enough inventory for not only what you’re selling out of the warehouse one, but also, what you’re selling out of Warehouse four, or 5, 6, and nine, five feeds nine.
So, when we do that, we model this is what you need, based on parameters that you set.
You may set a parameter that says, I’d like to keep 21 days of inventory, but if I get down, I get down below 14, bring me back up to 21.
So, the system’s going to constantly look to see do I have the minimum of 14 days of inventory?
If I don’t, here’s the quantity, I need to get to 21, then it goes and looks and says, well, do I have enough?
I know how much I would like to send, but if I don’t have enough, I’m going to look at every place that needs inventory. Let’s say warehouse 4 needs the most, warehouse 5 and 6 the least, but we’re going to take a ratio of what their need is to what inventory is available to send.
And we’re going to, we’re going to say that’s the quantity that you send to that spoke. So that’s a high-level look at hub and spoke.
It’s about all we could do in just a few minutes.
We have a number of products, so we’re just talking about demand planning, but now I would like to switch over to system itself, a chance to change some screen here.
Q: John, we had another question. Someone has asked, what’s the maximum number can hold or forecast on? Is there a limit?
Q: Well, there isn’t we haven’t found anybody that had too many items. We’ve had we do have customers who have hundreds of thousands of SKUs.
So, Um, we really have not run into the, you have too many.
See, let me show a screen.
There we go.
Demand Planning Demo
All right, So, now, we’re looking at demand planning, as I said, it runs inside of Business Central, and so this is where a buyer would spend their time. They would be saying, OK, what do I need to buy? And that’s where they go to the buying calendar. Also, on the screen is things like, here’s the inventory levels at my different warehouses, I can drill in and see the individual items and see something about the inventory. Here’s the history.
It’s a demo system, So, I only have one month of history, but I would see a bunch of history there.
Before I go look at what I need to buy, I’d like to just share with you, you know, a little bit about the formula. So, I’m going to look at, here’s my 18 formulas.
And so, its formula is the simple average of three months, three months with a trend, 60-day formula, six-month formula, six months with trend, an average with eliminate the high eliminate the low, an average eliminate the zero months.
And here’s an exponential smoothing formula, so, and we go down into the seasonal formula so you can see some are seasonal.
So, we look at this exponential smoothing formula which this one, and we’ll just take a look to see what does it looks like.
So, this is a weighted average.
We’re looking at month 1, 2, 3, 4, and five, which are past months.
Last month, two months, you know, back to five months ago, we’re putting a weight of 3, 2, and a half to 1.5 and 1 on each of those months to come up with a forecast.
And I’d say, well, why would you use that formula?
Remember we just talked about, it’s going to take this best fit saying, I tested this formula and it had the lowest error.
So, it’s going to test all of these formulas in an item by the formula comes up that says, this is the lowest median error, it’s going to pick.
So, let’s go look at it says here, how many times I only have a small database. But here’s how many times that formula was picked.
And if I wanted to, I could drill in and say, show me all the items the system assigned that formula.
So, look and see this formula on this item.
Just look at one.
This formula it says had a median error of 16.7. That was the best one.
So, when I go look at the forecasts, it’s going to show me a time-based plan showing me inventory forecast for the next 12 months.
So today I’m in February of 2021. So that’s my current month.
Those are my forecast numbers by month.
If I want to see those forecasts forecast with a graph this, should show me, graphically.
So, now this this block is the forecast and this thin line is the historical sales. So, I can easily see a picture of, you know, what is the forecast compared to actuals.
So, that’s just a very quick look at a single formula.
We do things with fact, we look at the forecast, and we look at our inventories, and we come up with, we know, what do I need to buy?
Here, we can see my customer orders, I can drill in and see well, with that 342, who are those customers. I can drill in. Here’s all my customers that are at open orders for this item.
So, now, I want to go take a look at, what do I need to buy?
So, you get a flavour of different things. So, here’s my, vendor buying calendars. So, this is a list.
This would run every night, be current first thing in the morning. And look at that, and say, here’s all my locations and the vendors that are associated with that.
And say, all right here, is this vendor I want to look at. I have 50 things I’ve been buying
I could have set a target.
You know, there’s a $10 million target, like, et cetera, targets gross weight, net weight, and volume.
Make sure that I hit that target when I place the order.
So, I’m going to go look at this suggested order. So, this is telling me there’s 50 different things I need to buy.
So here are all those things, the description, unit of measure, whether it’s critical or not, how many times they’ve sold in the past 12 months, how many I need to buy?
This tells me that there is a purchase order open right now.
This tells me if there’s any surplus available in another location, alerts they may have ,use the dollar amount, that fine.
If I want to see why do I need to buy 16,783?
Look at myforecast.
Here, it’s telling me: here’s my forecast.
I have these open Customer orders, collaborative, it would show here, any adjustments, shown here.
Here’s my inventory, seven and I have an open purchase order of 507.
So, it does the projected inventory, and it says, at my lead time horizon, which is nine, I’m going to have -16783. All right, and if I go look at my lead time, Lead time is 30 days.
I’m going out 30 plus 7 plus 50, so 87 days I go, 87 days, February 11th, it’s May 9th, that quantity there. So, when I order it, I’ll get it in about 30 days. So, I’ll get it about here.
I’m a bad shape.
I only have 507 on order, so this is an urgent thing, but there I review each of these items to whatever level I need to review them to see any kind of detail.
You know, what’s going on, why did it tell me to buy 300 or 98. Once I’m comfortable with that, I could make changes.
I come over here and I say, create the purchase order, the purchase order is created inside Business Central.
That means now we have an open purchase order that we send down to the vendor.
But this is, this is meant to present, you know, an intelligent story.
These are the items you need to buy, and, you can point and click to see, why do I need to buy, where is, you know, the demand coming from, what’s my history, what’s my open orders, is your collaborative.
It’s a good picture of why you should place your order. You can also do things like. add an additional item down here.
You say, Gee, I need to add this item. You can do that.
You can also buy from a different vendor, you know, even though it says you need to buy it from White World Importers today. There’s a way to click on here, override vendor number and say I’m going to buy it from somebody else.
I can also do transfers, so if there’s surplus, like here, there’s surplus inventory, I can click into this and say I’m going to take some of this inventory. So, let’s see what is this?
It says, I have 58 pieces, I could decide, I want to transfer it from another warehouse, And I could create a transfer along with the purchase order that I’m creating. So, that’s a very quick look at all that goes on with a suggested order.
I’d like to take another look at something else, surplus.
We calculate every night, you know, what is surplus and a lot of what we have Microsoft allows you to bring this to Excel.
So, we’re going to bring this to Excel.
She’s a whoops, I did this in a way.
I brought it to Word, not Excel, there’s a picture of my surplus. Let me do it again.
Let me do it again this time right now, essentially what I’m getting here Yeah, With?
I’m going to see all the items that are there in that warehouse, I picked one warehouse.
So now it’s telling me with a picture, I have other $187,000 of inventory, of which $60,000 is good.
This picture here, then, 43,000, a surplus, in 100,000 is excess If I want to I can drill in and see, you know, all of the detail.
I want to look little further on this, and I look down this column, and I say, OK.
Well, gee, right away There’s $91,000 of excess of this one item This item.
It’s a motor and here’s my 91,000 Oh, Uh, you know hundred thousand. I found most of in one item
You can do, whatever, you know, I need to know to look at this, something sometimes people will look at every month to see, is my inventory, you know, the right mix, the right inventory, or do I have some things, that may be excess?
So that’s one of the tools we map, so I’m going to leave a few minutes for questions.
Stop here, could go for a very long time, when, by the way, when we do demos for clients, prospects, it usually takes about 90 minutes.
So, we spent almost 30 minutes just hitting some interesting highlights that help you see what, what it is we do.
I’m going to leave a few minutes for questions if anybody has any questions. yeah. We’ve had a question come in I Can you set the MOQ and EOQ by item and also by vendor order total?
So, we do support economic order quantity, so, family inventory carrying cost and ordering cost and so, you can optionally use that on individual items. The system will support that. The minimum order quantity and multiple or we also support that.
So, you say: whenever I have this item, I order, you know, 48 cases. so, we can set a minimum of 48 and then say some multiple of something.
And so, all of your orders will be in those mins.
Um, didn’t talk a lot about assembly and production.
I suspect is probably at least some folks who are interested in that.
I’ll just, I’ll just go on a little bit for a couple of minutes. It there are any questions.
I’ll read them out as and when they come in.
So, if we will look at production, the system is going to create those simulated orders to support forecast an end item.
Then explode those into their raw components.
The whole purpose is to make sure that you have all those raw materials available for you when you decide to make your production, so.
Whenever I wanted to go quick, it goes slow.
So, here’s my list of production items.
So here is, let’s see, these are my simulated orders Ordetd at the end, these are the released order, so these are to be said released making this That’s 125 simulated plus 50 75, so if I were to go look to see, um, For this item.
Here’s where I see it. It Actually is component. This is a component. So, these quantities, there’s no forecasts, right? I don’t need any, because I don’t sell this.
And actually, I do have a sales order here, normally sell.
And so, I have 94 an inventory, but I need 108 and 134 to make something else.
Then, systems said, OK, whatever, they know these simulated orders. If I drill in and see this, it’s going to show me.
Here’s my simulated production orders. Click on the 50 one.
I can go see, there’s a simulated one and then it released one when I release a 50 and I can go and I can convert this simulated order to a released order.
If I so choose.
So, in the whole purpose of making sure that we create these simulated orders for whatever it is that’s needed, so that we can explode composite components, it’s a very quick look at production.
Instead, normally, we have a lot more time to explain in detail, but the system is going to erase all the simulated orders every night and then recreate them, support your current need, or forecast customer orders.
So, we have about a minute left.
Any other questions?
Q: And got another question, back to the wine example, can you have historical data by item? Have a forecast made by a recommended order by item group ie a set vintages?
Does that make sense?
You see that, again? Yeah. Can you have historical data by item but have a forecast made recommended order by item group, for example, a set of vintages.
Well, no, you can’t come up with a group forecast, but you can end the forecast, and you can review the group of items together to make sure that they, they add up to a meaningful number. I suspect that someone wants to say maybe 4 or 5 things they need to add up to a target quantity of some kind.
So, we give you the ability to add them up and make sure they hit the target, whether they be assembled, or production, or whether they be purchased.
But we don’t really support saying, we can forecast this group, we can add the forecasts up to see the total is.
But we’re not going to look at the combined history to come up with a good forecast.
OK, thank you.
I want to be respectful of your time, but I think we hit that 30 minutes. We have, I’ve said we’ve had several questions throughout. So, yeah, it’s time to finish that John, thank you once again for attending and delivering the webinar and the demo. If anyone has any further questions then, I’ll put them in touch with you and likewise, if anyone wants a more in-depth demo, we can get that arranged as well.
As with TVision webinars, the link will be sent out to everybody who registered very shortly and the transcript and recording will be available on the website soon. Than you once again, John, and thank you, everyone, for attending today.
Alright, thank you. Have a good day.