Microsoft Dynamics 365 BC and NAV can manage replenishment by suggesting what to order and when via reorder point-based inventory policies. The problem is that the ERP system requires that the user manually specify these reorder points and/or forecasts. As a result, most organizations end up forecasting and generating inventory policies by hand in Excel spreadsheets or using other ad hoc approaches. Given poor inputs, automatic order suggestions will be inaccurate, and in turn the organization will end up with excess inventory, unnecessary shortages, and a general mistrust of their software systems.  In this article, we will review the inventory ordering functionality in BC & NAV, explain its limitations, and summarize how Smart Inventory Planning & Optimization can help reduce inventory, minimize stockouts and restore your organization’s trust in your ERP by providing the robust predictive functionality that is missing in Dynamics 365.

Microsoft Dynamics 365 BC and NAV Replenishment Policies

In the inventory management module of NAV and BC, users can manually enter planning parameters for every stock item. These parameters include reorder points, safety stock lead times, safety stock quantities, reorder cycles, and order modifiers such as supplier imposed minimum and maximum order quantities and order multiples.  Once entered, the ERP system will reconcile incoming supply, current on hand, outgoing demand, and the user defined forecasts and stocking policies to net out the supply plan or order schedule (i.e., what to order and when).

There are 4 replenishment policy choices in NAV & BC:  Fixed Reorder Quantity, Maximum Quantity, Lot-For-Lot and Order.

• Fixed Reorder Quantity and Max are reorder point-based replenishment methods. Both suggest orders when on hand inventory hits the reorder point.  With fixed ROQ, the order size is specified and will not vary until changed.  With Max, order sizes will vary based on stock position at time of order with orders being placed up to the Max.
• Lot-for Lot is a forecasted based replenishment method that pools total demand forecasted over a user defined time frame (the “lot accumulation period”) and generates an order suggestion totaling the forecasted quantity. So, if your total forecasted demand is 100 units per month and the lot accumulation period is 3 months, then your order suggestion would equal 300 units.
• Order is a make to order based replenishment method. It doesn’t utilize reorder points or forecasts. Think of it as a “sell one, buy one” logic that only places orders after demand is entered.

Limitations

Every one of BC and NAVs replenishment settings must be entered manually or imported from external sources.  There simply isn’t any way for users to natively generate any inputs (especially not optimal ones). The lack of credible functionality for forecasting and inventory optimization within the ERP system is why so many NAV and BC users are forced to rely on spreadsheets.  Planners must manually set demand forecasts and reordering parameters.  They often rely on user defined rule of thumb methods or outdated and overly simplified statistical models.  Once calculated, they must input the information back into their system, often via cumbersome file imports or even manual entry.  Companies infrequently compute their policies because it is time consuming and error prone. We have even encountered situations where the reorder points haven’t been updated in years. Many organizations also tend to employ a reactive “set it and forget it” approach, where the only time a buyer/planner reviews inventory policy is at the time of order–after the order point is already breached.

If the order point is deemed too high, it requires manual interrogation to review history, calculate forecasts, assess buffer positions, and to recalibrate.  Most of the time, the sheer magnitude of orders means that buyers will just release it creating significant excess stock.  And if the reorder point is too low, well, it’s already too late. An expedite is required to avoid a stockout and if you can’t expedite, you’ll lose sales.

Get Smarter

Wouldn’t it be better to simply leverage a best of breed add-on for demand planning and inventory optimization that has an API based bidirectional integration? This way, you could automatically recalibrate policies every single planning cycle using field proven, cutting edge statistical models.  You would be able to calculate demand forecasts that account for seasonality, trend, and cyclical patterns.  Safety stocks would account for demand and supply variability, business conditions, and priorities.  You’d be able to target specific service levels so you have just enough stock.  You could even leverage optimization methods that prescribe the most profitable stocking policies and service levels that consider the real costs of carrying inventory. With a few mouse-clicks you could update NAV and BC’s replenishment policies on-demand. This means better order execution in NAV and BC, maximizing your existing investment in your ERP system.

Smart IP&O customers routinely helps customers realize 7 figure annual returns from reduced expedites, increased sales, and less excess stock, all the while gaining a competitive edge by differentiating themselves on improved customer service.

To see a recording of the Dynamics Communities Webinar showcasing Smart IP&O, register here:

https://smartcorp.com/inventory-planning-with-microsoft-dynamics-nav/

In Smart Software’s forty-plus years of providing forecasting software, we’ve met many people who find themselves, perhaps surprisingly, becoming demand forecasters. This blog is aimed primarily at those fortunate individuals who are about to start this adventure (though seasoned pros may enjoy the refresher).

Welcome to the field! Good forecasting can make a big difference to your company’s performance, whether you are forecasting to support sales, marketing, production, inventory, or finance.

There is a lot of math and statistics underlying demand forecasting methods, so your assignment suggests that you are not one of those math-phobic people who would rather be poets. Luckily, if you are feeling a bit shaky and not yet healed from your high school geometry class, a lot of the math is built into forecasting software, so your first job is to leave the math for later while you get a view of the big picture. It is indeed a big picture, but let’s isolate few of the ideas that will most help you succeed.

1. Demand Forecasting is a team sport. Even in a small company, the demand planner is part of a team, with some folks bringing the data, some bringing the tech, and some bringing the business judgment. In a well-run business, your job will never be to simply feed some data into a program and send out a forecast report. Many companies have adopted a process called Sales and Operations Planning (S&OP) in which your forecast will be used to kick off a meeting to make certain judgments (e.g., Should we assume this trend will continue? Will it be worse to under-forecast or over-forecast?) and to blend extra information into the final forecast (e.g., sales force input, business intelligence on competitors’ moves, promotions). The implication for you is that your skills at listening and communicating will be important to your success.

2. Statistical Forecasting engines need good fuel. Historical data is the fuel used by statistical forecasting programs, so bad or missing or delayed data can degrade your work product. Your job will implicitly include a quality control aspect, and you must keep a keen eye on the data that are supplied to you. Along the way, it is a good idea to make the IT people your friends.

3. Your name is on your forecasts. Like it or not, if I send forecasts up the chain of command, they get labeled as “Tom’s forecasts.” I must be prepared to own those numbers. To earn my seat at the table, I must be able to explain what data my forecasts were based on, how they were calculated, why I used Method A instead of Method B to do the calculations, and especially how firm or squishy they are. Here honesty is important. No forecast can reasonably be expected to be perfectly accurate, but not all managers can be expected to be perfectly reasonable. If you’re unlucky, your management will think that your reports of forecast uncertainty suggest either ignorance or incompetence. In truth, they indicate professionalism. I have no useful advice about how best to manage such managers, but I can warn you about them. It’s up to you to educate those who use your forecasts. The best managers will appreciate that.

4. Leave your spreadsheets behind. It’s not uncommon for someone to be promoted to forecaster because they were great with Excel. Unless you are with an unusually small company, the scale of modern corporate forecasting overwhelms what you can handle with spreadsheets. The increasing speed of business compounds the problem: the sleepy tempo of annual and quarterly planning meetings is rapidly giving way to weekly or even daily re-forecasts as conditions change. So, be prepared to lean on a professional vendor of modern, scalable cloud-based demand planning and statistical forecasting software for training and support.

5. Think visually. It will be very useful, both in deciding how to generate demand forecasts and in presenting them to management, so take advantage of the visualization capabilities built into forecasting software. As I noted above, in today’s high-frequency business world, the data you work with can change rapidly, so what you did last month may not be the right thing to do this month. Literally keep an eye on your data by making simple plots, like “timeplots” that show things like trend or seasonality or (especially) changes in trend or seasonality or anomalies that must be dealt with. Similarly, supplementing tables of forecasts with graphs comparing current forecasts to prior forecasts to actuals can be very helpful in an S&OP process. For example, timeplots showing past values, forecasted values, and “forecast intervals” indicating the objective uncertainty in the forecasts provide a solid basis for your team to fully appreciate the message in your forecasts.

That’s enough for now. As a person who’s taught in universities for half a century, I’m inclined to start into the statistical side of forecasting, but I’ll save that for another time. The five tips above should be helpful to you as you grow into a key part of your corporate planning team. Welcome to the game!

Extend Epicor Kinetic’s Forecasting & Min/Max Planning with Smart IP&O  
Epicor Kinetic can manage replenishment by suggesting what to order and when via reorder point-based inventory policies. Users can either manually specify these reorder points or use a daily average of demand to dynamically compute the policies.  If the policies aren’t correct then the automatic order suggestions will be inaccurate, and in turn the organization will end up with excess inventory, unnecessary shortages, and a general mistrust of their software systems.  In this article, we will review the inventory ordering functionality in Epicor Kinetic, explain its limitations, and summarize how Smart Inventory Planning & Optimization (Smart IP&O) can help reduce inventory, minimize stockouts and restore your organization’s trust in your ERP by providing the robust predictive functionality that is missing from ERP systems.

Epicor Kinetic (and Epicor ERP 10) Replenishment Policies
In the item maintenance screen of Epicor Kinetic, users can enter planning parameters for every stock item. These include Min On-Hand, Max On-Hand, Safety Stock lead times, and order modifiers such as supplier imposed minimum and maximum order quantities and order multiples.  Kinetic will reconcile incoming supply, current on hand, outgoing demand, stocking policies, and demand forecasts (that must be imported) to net out the supply plan.   Epicor’s time-phased replenishment inquiry details what is up for order and when while the Buyers Workbench enables users to assemble purchase orders.

Epicor’s Min/Max/Safety logic and forecasts that are entered into the “forecast entry” screen drives replenishment.  Here is how it works:

• The reorder point is equal to Min + Safety. This means whenever on hand inventory drops below the reorder point an order suggestion will be created. If demand forecasts are imported via Epicor’s “forecast entry” screen the reorder point will account for the forecasted demand over the lead time and is equal to Min + Safety + Lead time forecast
• If “reorder to Max” is selected, Epicor will generate an order quantity up to the Max. If not selected, Epicor will order the “Min Order Qty” if MOQ is less than the forecasted quantity over the time fence. Otherwise, it will order the forecasted demand over the time-period specified.  In the buyer’s workbench, the buyer can modify the actual order quantity if desired.

Limitations
Epicor’s Min/Max/Safety relies on an average of daily demand. It is easy to set up and understand.  It can also be effective when you don’t have lots of demand history. However, you’ll have to create forecasts and adjust for seasonality, trend, and other patterns externally.  Finally, multiples of averages also ignore the important role of demand or supply variability and this can result in misallocated stock as illustrated in the graphic below: 

In this example, two equally important items have the same average demand (2,000 per month) and safety stock is determined by doubling the lead time demand resulting in a reorder point of 4,000. Because the multiple ignores the role of demand variability, Item A results in a significant overstock and Item B results in significant stockouts.

As designed, Min should hold expected demand over lead time and Safety should hold a buffer. However, these fields are often used very differently across items without a uniform policy; sometimes users even enter a Min and Safety Stock even though the item is being forecasted, effectively over estimating demand! This will generate order suggestions before it is needed, resulting in overstocks.  

Spreadsheet Planning
Many companies turn to spreadsheets when they face challenges setting policies in their ERP system.  These spreadsheets often rely on user defined rule of thumb methods that often do more harm than good.  Once calculated, they must input the information back into Epicor,  via manual file imports or even manual entry.  The time consuming nature of the process leads companies to infrequently compute their inventory policies – Many months of even years go by in between mass updates leading to a “set it and forget it” reactive approach, where the only time a buyer/planner reviews inventory policy is at the time of order.  When policies are reviewed after the order point is already breached it is too late.  When the order point is deemed too high, manual interrogation is required to review history, calculate forecasts, assess buffer positions, and to recalibrate.  The sheer volume of orders means that buyers will just release orders rather than take the painstaking time to review everything leading to significant excess stock.  If the reorder point is too low, it’s already too late.  An expedite is now required driving up costs and even then you’ll still lose sales if the customer goes elsewhere.

Epicor is Smarter
Epicor has partnered with Smart Software and offers Smart IP&O as a cross platform add-on to Epicor Kinetic and Prophet 21 with API based integrations.  This enables Epicor customers to leverage built for purpose best of breed forecasting and inventory optimization applications.  With Epicor Smart IP&O you can automatically recalibrate policies every planning cycle using field proven, cutting-edge statistical and probabilistic models.  You can calculate demand forecasts that account for seasonality, trend, and cyclical patterns.  Safety stocks will account for demand and supply variability, business conditions, and priorities.  You can leverage service level driven planning so you have just enough stock or turn on optimization methods that prescribe the most profitable stocking policies and service levels that consider the real cost of carrying inventory. You can build consensus demand forecasts that blend business knowledge with statistics, better assess customer and sales forecasts, and confidently upload forecasts and stocking policies to Epicor within a few mouse-clicks.

Smart IP&O customers routinely realize 7 figure annual returns from reduced expedites, increased sales, and less excess stock, all the while gaining a competitive edge by differentiating themselves on improved customer service. To see a recorded webinar hosted by the Epicor Users Group that profiles Smart’s Demand Planning and Inventory Optimization platform, please register here: https://smartcorp.com/epicor-smart-inventory-planning-optimization/