Is your inventory management run on gut feel and guesswork?
Maybe it’s based on an outdated demand-planning package that no-one knows how to reconfigure to meet today’s needs. With Brexit and Covid-19 combining to create a perfect storm in logistics, forecasting and demand planning are both more vital and more difficult than ever. So, let’s take a look at what’s involved and some of the keys to success.
Forecasting and demand planning has always been important in business.
Before the age of IT, this activity was something of a black-art, based on intuition and historical sales. In the digital age, there is a wealth of information to feed into these predictions. Judging the weight that should be accorded to each stream of data is tricky. Throw in a good measure of economic uncertainty and things get really difficult.
In a downturn, cash is king. Tying up working capital in unnecessary stock could be very damaging. However, with coronavirus having disrupted supply chains and no-deal Brexit threatening delays at ports and airports, holding some buffer stock seems desirable. Optimising inventory through accurate forecasting and demand planning may be the difference between survival and demise for many in the current climate.
Without these predictions, how can firms plan when and what to manufacture, buy and stock?
Forecasting and demand planning Plans: ‘push’ versus ‘pull’
We are already surrounded by plans.
The finance department produces detailed financial forecasts for the business. The marketing and sales teams quite often produce selling forecasts and sales forecasts. The production planner painstakingly calculates requirements and outputs in a production plan. There are marketing plans and customer account plans, detailing when and what will be promoted. Strategic plans are also in the mix as management try to steer the ship.
However, all these plans are rarely integrated and the objectives and targets in each are often contradictory.
Many sales and production plans are ‘push’ plans, aimed at selling or producing as much as possible.
Why? Because sales teams believe they will sell more and must have the stock to meet their orders. Meanwhile, production plans are designed to maximise output and minimise production costs.
Demand planning, on the other hand, encourages businesses to look at the factors that are ‘pulling’ actual sales. Consumer demand and specific promotional response are great examples. Then production and supply chain resources can be adjusted accordingly.
Switching the focus to an analysis of demand can bring numerous benefits, not least:
- Increased customer service with reduced inventory levels
- Improved supply chain capacity and cost control
- Increased supply chain responsiveness and flexibility
Sounds counter-intuitive? It has been proven not to be. It’s a fact that companies often do not have the stock they need to sell today but they do have plenty of stock that is not selling.
Demand planning allows the business to review an integrated plan on a regular basis. This will bring together sales, production and financial plans. Now you can add in up-to-date demand information and produce a single, more accurate forecast that can satisfy the requirements of all departments and customers. Safety stocks are calculated from real data.
With a realistic lead time from production order to warehouse delivery, stocks can be planned that will allow the customer service objectives to be met.
Under-forecasting and over-forecasting
Forecasting future demand reasonably accurately is key to the process of demand and supply chain management. However, forecasting is never perfect; errors can result from either under-forecasting or over-forecasting. Shortfalls from under-forecasting can be made good through increases in production and shipment costs, although there can be lost sales.
In the case of over-forecasting, losses to the business come from discounts that must be offered to dispose of excess or obsolete inventory. Losses also come from the cost of holding excess stock or transhipping products from one distribution centre to another.
Few companies realise the true cost of holding inventory. Until it is used or sold, the inventory provides no value to an organisation. There is a cost to holding it (warehousing and storage costs). Product lifecycle can result in stock being thrown away.
Inventory is an investment that must be financed. This can be done either by borrowing (at the cost of interest) or from the company’s funds (at the cost of lost interest and the lost opportunity to use this capital elsewhere, such as investing in production capacity).
So, efficient supply chains must maintain the lowest possible inventory consistent with the highest possible service levels that match the company’s objectives, whilst keeping costs down. The short-term benefits include improvements to the planning of transport, inventory requirements, production schedules, capacity, manpower, sales and marketing, purchasing and finance/budgeting.
In the longer term, the systems and data gathering provided by this process can be used for business modelling and ‘what-if?’ analyses.
Forecasting and demand planning tools are widely available, and many ERP systems have demand planning features. However, forecasting software alone is unlikely to provide the hoped-for improvements; it must be linked into a recognised company-wide process of sharing information and making (joint) decisions. To implement this into a business there are a number of pre-requisites:
- Defined processes
- Defined responsibilities tied to performance incentives
- A forecasting tool (and training) and appropriate links/interfaces
- Training support
A demand forecast will be based on a statistical analysis of historical information combined with future assumptions. It will be based on a number of drivers. Examples will include market development, promotions, new product launches, competitive and seasonal activity and peak periods such as Easter, Christmas or the start of the school/university year.
The business needs to identify the departments that are responsible for deciding or monitoring these specific drivers. Individual roles and responsibilities need to be updated to reflect driver-related objectives. Compensation and incentives programmes need to be adjusted and aligned across the company.
As a starting point, the top drivers in each area should be identified. This allows the business to concentrate on the most important focus areas right away. Over time, additional drivers should be identified and included in the demand management process.
It is particularly important that all departments co-operate in driver identification and subsequent assumption management. Demand forecasting is not simply a sales function and cannot be used successfully without input from many sources.
The demand forecasting and planning process
On a periodic, often monthly basis, the demand forecasting and demand management process should be performed with the least loss of time. It should then be integrated with the other reporting processes in the Company.
Forecasting models that take too long to produce becomes useless as a predictive and tracking tool. Remember also, have a sense of proportionality: forecasting to 3 decimal points of a case (if that is your sales unit to your customers) is a waste of time.
You can easily be over-academic; remain practical.
There are three phases:
- Produce a statistical demand forecast based on known history and existing assumptions. Commercially available tools exist to calculate the best forecast available. This is usually based on past history, combined with the known effect of forthcoming events. This might include new product launches, production issues and holiday periods.
- Undertake a demand forecast review and demand management analysis. A forecast analyst will review the forecast and add any other factors based on market intelligence that may cause a variance to demand. Examples would include competitor activity or regional events.
In a many-SKU business, this manual review can be quite time-consuming. Shortcuts will need to be found to minimise the turnaround time. Focusing on fast-moving items or known problem areas could be considered. A cross-functional management team must meet to review and approve the forecast.
- Consolidate, adopt and upload the forecast. Once approved, the forecast data will be combined with company strategy (e.g. customer service levels to be achieved and levels of inventory of raw materials and finished goods) and turned into purchase orders, production plans, manpower and resource plans, transport plans, etc.
Statistical forecasting – Enhancing the process
Forecast accuracy can be monitored by comparing actuals with the original forecasts.
Targets must be set to improve forecast accuracy. Every effort made to determine what causes variations in demand so that these fluctuations can be recorded and used in future planning cycles. Likewise, production outturns need to be compared with the plan and stockouts need monitoring, as do levels of obsolete stocks.
Of course, once this process is adopted, it has to be accompanied by the willingness and ability to react flexibly to short-term changes in forecast demand.
In summary, the key messages are:-
- Effective demand planning can help to improve and/or even save the business
- For planning to be effective, it must be driven by truly cross functional engagement throughout the business.
- To be effective, demand planning must be carried out regularly and as frequently as is compatible with other key operations of the business.
- For effective demand planning to help the business it is best initiated sooner rather than later.
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