Demand planning food manufacturing
Expert Demand Planning for food manufacturing, food processing, food packing & distribution.

Expert Demand Planning for food manufacturing


Order Validity Analysis. The final piece of the demand planning pie — where profitable, efficient orders happen.

Order Validity Analysis allows you to place an order that makes sense for your receiving team, keeps your line in balance, and ensures that the order comes due in harmony the next time.

Order Validity Analysis happens after basic replenishment, and after you have taken advantage of any deals, prepared for promotions, and considered overstock options.

  1. Demand Forecasting
  2. Lead Time Forecasting
  3. Order Cycle Optimization
  4. Service Level Management
  5. Replenishment
  6. Special Order Analysis
  7. Order Validity Analysis

Expert Demand Planning for food manufacturing

Avoid Constraints
and Bottlenecks

When communicating in real-time across your complex supply chain, you quickly gain flexibility.

  • Include ERP inputs to better manage material and capacity constraints.
  • Predict and forecast using advanced analytics to align demand and supply.
  • Review and iteratively optimize planning based on trends and KPIs you set.

Create Impactful

Keeping up with changing customer tastes is easier than ever. Monitor trends and adapt your plans to max out yield.

  • Zero in on demand patterns, trends, and seasonality.
  • Project revenue and margin at any level of aggregation.
  • Realize deeper understanding of your supply chain with demand-shaping and sensing data.
  • Liberate teams and eliminate silos to drive collaboration.

Proactively Manage Your
Supply Chain

Stay on top of all your branded consumer products and maintain compliance without missing a beat.

  • Anticipate demand and stock strategically with agile planning.
  • Optimize inventory to reduce cost and improve lead times.
  • Make your demand and supply plan proactive with regular S&OP processes.


How an accurate estimation of the future demand can reduce wastefulness

In this post we’ve talked about the demand forecasting for manufacturing. But now, let’s go in deep considering one of the biggest industry in the manufacturing area, the food industry, with more than 2 trillion dollars of sales in the United States in 2016. Like in the other manufacturing areas, all the activities of the supply chain are managed and planned following an estimation of the future demand the manufacturer aims to satisfy, in order to avoid losing sales and even customers. However, in the food industry, there is another big challenge besides meeting the demand and avoiding extra levels of stock, for which demand forecasting could be crucial: the short perishability of goods.

Demand Forecasting For Food Manufacturers image

It’s a matter of time

That is, when an expiration date is assigned to a product, the time spent on a shelf or in a refrigerator affects negatively its duration. Thus, the stock cost is not the sole problem in this case. So, in the food industry, the production of goods have to reflect the incoming demand, since the out of stock scenario is not desirable and goods should be sold at the beginning of their lifetime, without stocking them one upon the other over time.

However, this is a really hard goal to reach for manufacturers and production planners. A demand forecasting tool can address such problem, although it couldn’t solve it at all (unless it makes use of a crystal ball). It’s important to keep in mind that perfection is not the point in this case, since it is unreachable. In this case, the only thing which really matters is to gradually reduce the waste of goods with a more accurate estimation of the future demand.

A more accurate estimation of the future demand leads to a better inventory optimization of raw materials from one hand and to a production planning which optimizes the stock levels of finished products from the other hand. Thus reducing lost sales and too-long-stock-time of goods with a short perishability.

This is why a demand forecasting tool can be useful for an improved supply chain management.

Optimized Buying Multiples, Balanced Orders, Intelligent Brackets

Best-in-class demand planning carries the process through to completion for inventory teams. There should not be a need for manual adjustments for buying multiples, or for building to brackets.

Finish the order by executing the previous established, intelligent parameters.

#7 is Executing the Chosen Elements of #3:  Order Cycle Optimization

Order Validity Analysis: 7 Essential Steps to Expert Demand Planning
Order Validity Analysis: 7 Essential Steps to Expert Demand Planning

It’s important to recognize that Element #7 is a process of executing the decisions already made during Element #3:  Order Cycle Optimization. During Element #3, you chose the most profitable Order Cycle, as well as the most profitable Order Minimum or Bracket. You also made sure that the chosen Order Cycle time supply matched the chosen Bracket.

For example, if the most profitable bracket is a truckload, and it takes 10 days to sell a truckload of product, then the Order Cycle must be 10 days.

During Element #7, you ensure that the order total matches the chosen bracket of a truckload. In addition, you’ve already chosen item Buying Multiples and even Convenience Multiples for each item. During Element #7, you will round the order quantities required  to their chosen multiples.

Element #7 is not a time for last-minute changes due to freelance rounding to multiples. It is a time to execute the plan.

Three Main Areas of Focus:

  1. Adhere to the Chosen Bracket
  2. Build Days in Balance to the Chosen Bracket
  3. Round Item Quantities to Buying Multiples & Convenience Multiples

Adhere to the Chosen Bracket

Through the first 5 elements, fresh produce inventory you created order quantities needed to maintain your service level goals. In the 6th element, you adjusted items for any deals, planned promotions and overstock balancing decisions.

Now it’s time to add up all of those quantities and see how the totals compare to the bracket requirements. These are streamlined, important decisions in this final stretch.

Your needs total 38,000 lbs. The chosen bracket is 44,000 lbs. There is still work to be done!

Build Days in Balance to the Chosen Bracket

Building days in balance is the key.

Avoid simply adding quantity to your top item or two to achieve the total. This puts the line out of balance. And after doing this for a few orders in a row, you will have so much excess of those A items, that you won’t have enough weight to build an order. All other items will be harmed.

Remember, one of the most important goals you have in this process is to build the order in such a way that you are well prepared for the next order. You are preparing for the next order as much as you are trying to complete this order.

Both goals are equally as important.

Order Validity Analysis: 7 Essential Steps to Expert Demand Planning
Order Validity Analysis: 7 Essential Steps to Expert Demand Planning

To build the order up, you will increase your Vendor Order Point, as well as your Order Up To Level one day at a time (or a fractional day at a time).

The obvious move is to increase the OUTL for each item being bought; however, this is not enough. As shown in the visual above, this example required 4 additional days to reach the truckload bracket. By also increasing the Vendor Order Point, some items that were not previously needed on the order are now needed.

This is one of the critical steps that keeps the line balanced.

There are 2 pitfalls you need to watch out for here: mismatch and strategy change…

AVOID Mismatch:  If you find that you are continuously adding numerous days’ supply to achieve the minimum or bracket, it is possible that your Order Cycle is not set properly to match the bracket. Once you know that you have to achieve a minimum or bracket, you have to make sure the days’ supply matches it.

AVOID Strategy Change:  This final step is not the time to determine that which bracket is right for you. That decision should have occurred during Element #3 – Order Cycle Optimization. Once that bracket is chosen, the Order Cycle was set to match it.

There may be unique times of the year where you will decide to make unique decisions, or even to forego a bracket to bring in needed items when achieving

Order Validity Analysis: 7 Essential Steps to Expert Demand Planning
Order Validity Analysis: 7 Essential Steps to Expert Demand Planning

the bracket requires too many days. This can occur after large forward-buy orders have been placed.

Round Item Quantities to Buying Multiples & Convenience Multiples

As the items are moving up the depletion graph to achieve the supplier minimum or bracket, each item also has to abide by its chosen rounding multiple rules.

The obvious process is to adjust each order quantity to round to the buying multiple. The more important Buying Multiple decision should have happened back during Element #3:  Order Cycle Analysis.

Many items have several choices of buying multiples, including eaches, cases, layers and pallets. Some suppliers force requirements on certain items. These requirements can lead to critical decisions of centrally stocking the item, or even not stocking the item.

Some items also have unique item minimums. This is most common with private-label suppliers who have to make special equipment adjustments to their manufacturing processes.

Time to Revisit Your Buying Multiple Strategy

It is important to choose intelligent and financially smart buying multiples. The following Buying Multiple strategy has been deployed by a best-in-class inventory team in the foodservice distribution industry.

You see a cascading approach where the faster moving items, which are likely holding the most dollars, are rounding to only 2 days supply. This keeps the line balanced and the items closest to the Order Up To Level when replenishing.

Order Validity Analysis: 7 Essential Steps to Expert Demand Planning
Order Validity Analysis: 7 Essential Steps to Expert Demand Planning

Watch for These Buying Multiple Pitfalls…

Buying Multiples Take the Lead:  The Buying Multiple becomes the Order Cycle. Normally, your supplier order cycles drive your replenishment, but when A-items have large buying multiples in days, those buying multiple become the true order cycle, and it is much higher. This drives inventory up.

You might think your Order Cycle is 14 days, but your Effective Order Cycle might actually be 21 days due to high buying multiples on A items.

Out of Balance:  Inconsistent Buying Multiple Days throws the line out of balance. When a line is replenished, your strategy is trying to buy everything to the same Order Up To Level.   If all of your items in the supplier line sit at high buying multiple days, they will also all be at different buying multiple days. This leads to heavy inventories.

Too Much Topping Off of Your High-Inventory A-Items:  Often many A-items sit just a few days below the Order Up To Level with very little need. However, when they are replenished back up, they are forced to go many days or weeks beyond the desired Order Up To Level.

These high inventory items are being ‘topped off’ and never deplete down to the lower level where they could be living. This also leads to heavier inventories.

The Key to Smart Multiples is Smart Convenience Multiples

The key to not applying costly, high buying multiples is to apply a Convenience Multiple option.

Trying to choose between buying in layers and pallets? Set your Buying Multiple to layers and apply a pallet-level Convenience Multiple.

When the need drives the order quantity close to the pallet, make the jump to the pallet size. Best-in-class demand forecasting solutions will have this feature, and will allow you to set your ‘aggressiveness level’ of when to make the jump.

Great demand planning teams set smart Buying Multiples and Convenience Multiples and adjust them as the demand changes, including seasonal adjustments. Processes can be put in place to make this process very fluid.

Success Will Come from Finishing the Process with Great Precision

Avoid emotional and tactical decisions and allow your #3 Order Cycle strategy settings to work. Watch for the pitfalls of too many days added to an order, and rounding too high on expensive A items.

These 7 Essential Elements will help you avoid numerous demand planning snafus and deliver rapid results in service, inventory and profit.

Even the top inventory teams in the world continually challenge their level of excellence in each element.

Food Manufacturers Turn to Demand Forecasting to Gain a Competitive Edge

For many manufacturers, the business landscape has changed dramatically over the past several years. Not only have we endured a downturn in the economy, causing increased competition, but we have now been put in the position to deal with soaring increases in raw material, energy and transportation costs.

Mar 9th, 2006

For many manufacturers, the business landscape has changed dramatically over the past several years. Not only have we endured a downturn in the economy, causing increased competition, but we have now been put in the position to deal with soaring increases in raw material, energy and transportation costs.

So how can food manufacturers, in particular, gain a competitive advantage while maintaining high service levels and healthy margins? Certainly brand management, quality, and even culture are long-standing core competencies. But from a process perspective, the ability to accurately predict demand in the wake of inflation can make the biggest difference.

When speaking to food manufacturers around the world, demand forecasting seems to be a prominent issue that keeps them up at night. Yet, while many companies consider demand forecasting important, several still are not addressing it through improvement programs. The problem sometimes stems from a lack of understanding of how to improve forecast accuracy (or that it can be improved), as well as what the improvement is worth in terms of profit and asset utilization.

Demand forecasting helps companies in several readily apparent areas, such as production, scheduling and customer service. Food manufacturers have traditionally found that there is usually an obvious increase in inventory associated with customer service level improvements. However, being able to rebalance or reclassify inventory as a result of improved forecast accuracy can produce significant improvements in customer service without increasing overall inventory value.

The ability to produce these improvements even as raw material costs increase is a real attention-getter for several food manufacturers, including a recent Silvon Software customer for which raw materials represent the second largest cost after labor. This food manufacturer has a lot of perishable product moving from plants to distribution centers to stores around the country. If its forecast is off by as little as one percent, the company’s fuel and packaging costs can soar, quickly bleeding the bottom line. This is especially true today, since the wildly fluctuating cost of oil affects not only transportation costs, but also the cost of film used to package products. Just because this company’s fuel costs may be rising, that doesn’t mean it can go to a mass merchandiser, such as Wal-Mart, and raise its prices. The end result would be lost shelf space, as competitors who did a more effective job of demand management are able to deliver product to the mass merchandisers at a lower cost.

Another issue is promotional periods. If a food manufacturer underestimates forecasts for key promotional periods such as holidays, mass merchandisers will quickly turn to other suppliers for product - and those same merchandisers will remember the manufacturer’s shortfall the next time a promotional period hits. For instance, ricotta cheese is very popular just before Easter and Thanksgiving. For a company in the dairy business, if it doesn’t hit those promotional periods on time, it can lose its shelf space quickly – and perhaps, for a long time.

How important is it to accurately predict demand during promotional periods? According to a recent Grocery Manufacturers of America survey, stockout rates for promoted items are two times the level of the stockout rates for non-promoted items. Food manufacturers who are not using demand management tools to predict the lift they receive from a promotion are often very surprised when they find out they have underestimated the forecast of consumer demand. Some other stats from the survey that stand out:

• Consumers cannot find promoted items 7.4 percent of the time due to stockouts.
• If an item is out of stock, 62 percent of shoppers will substitute for it with another product. That kills customer loyalty.
• If a customer cannot find a product, 23 percent of them will go to another retailer just to buy the product they were looking for.
• Bottom line – the GMA survey found that stockouts result in $6 billion in losses annually – all because companies underestimate the demand forecast and can’t supply the customer.

But while many food manufacturers are familiar with the perils of underforecasting, many are also hurt just as much by overforecasting. For instance, one food manufacturing customer of Silvon Software produces a product with a supermarket shelf life of seven days. If it overestimates forecasts, the product has to be thrown out within a week. The substantial costs related to this makes it imperative that the company not overestimate forecasts of this product.

Another problem of overforecasting is wasted packaging. If a product doesn’t sell and 4 million impressions of film for that product have been ordered, the company is stuck with years of packaging supply. That’s a big problem made even worse when changes in labeling rules result in some companies having to completely throw out millions of dollars in packaging…all because forecasts were overestimated.

The approach many food processors are adopting is an internal collaborative demand forecasting process, driven by a statistical forecasting model. In today’s world of Supply Chain tools, users need only a rudimentary knowledge of data analysis and statistics. They should be expected to deal primarily with exceptions to the forecasting process, driven by predetermined business rules, such as absolute forecast error.

By no means is demand forecasting a black-box approach (nor will it ever be), but the analytical heavy lifting can be done with software tools. Not only that, but the results can be measured to determine the trust to place in the process and when to use internal experts. In fact, measuring forecast accuracy at all levels of detail will, in and of itself, drive improvements.

Surprisingly, many food manufacturing companies still have not made demand forecasting a core competency. Those food manufacturers that have are more competitive, more agile and more profitable in today’s demand-driven world.


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