The pitfalls of automating replenishment ordering and how to avoid them
Clients thinking of automating their replenishment processes often ask me what potential problems they should be alert to when changing their systems. It’s a good question because the pitfalls and challenges always seem to be the same regardless of the industry and they normally boil down to three things:
- Accuracy of master data
- Assortment Management
- Change Management
Accuracy of Master Data
When moving to automated ordering the accuracy of master data becomes significantly more important.
For normal ordering rows the objective is a smooth process from order proposal straight to purchase order, without further analysis. If the balances or delivery times are unrealistically optimistic, the resulting order proposals may lead to availability problems.
Problems also occur if other basic information, for example a product’s listed size or supplier details, is incorrect. Where data is inaccurate an error is sometimes picked up during manual order processing. But where ordering is automated the system takes bad data at face value and the order may well get stuck later in the process.
Worse still, incorrect master data can lead to a breakdown of trust, with the replenishment system being seen by the purchasing manager as ‘the enemy’. The system risks getting blamed for every error; ”the system screwed up the ordering again”.
It may lead some managers to conclude that manual ordering is superior to automated ordering. That’s like assuming that walking is quicker than taking your Ferrari because the oil you put in its engine had grit in it and the car seized up. Put in decent oil and fuel and run that race again. No contest.
Getting master data to a workable level may take a lot of effort. That stage is a manual process and it’s the stage where error checking needs to be done. But once the initial challenges have been met things usually start running smoothly. Many of our clients find that automation has provided the impetus needed to improve their master data. That in turn improves other processes within the company. In practice the other two pitfalls I highlighted generally prove tougher to deal with.
Manual ordering inevitably has a human dimension. Some stores and product managers make assortment decisions ‘on the fly’ while ordering. Products that should be in the assortment are dropped because they are ‘no longer in season’, demand is ‘poor’ or because the purchasing manager has a ‘gut-feeling’ (”these types of products don’t sell”). At the same time, products outside the defined range have been ordered because a whole product line is experiencing a growing demand, or again, just based on that same ‘gut feeling’ (”what an exciting new product, we could try this”).
The goal of automated ordering is to provide the most efficient way of making a specified assortment of products available on your shelves at a given time, for example; continuously throughout a particular season or during weekends only. To achieve a high level of automation it is very important that the assortment is defined for each individual location and that assortment decisions are made separately from the ordering process. Otherwise the saved time is wasted when the client making the order has to go through the order proposal one row at a time.
Thanks to automated ordering the assortment range can be defined even more accurately. The ordering system ensures that the correct assortment is assigned to the shelf at the defined location – no more, no less.
For many clients automated ordering has made it necessary that product assortment decisions are more process-oriented and accurate way than before. Often this results in a shift in who is responsible within an organisation for determining assortments. The reassignment of tasks and responsibility can cause minor or even major friction in a company. That takes us to the third and most challenging stage: Change Management.
When ordering is automated, the roles and responsibilities of many employees change. At the very least tasks are reprioritised. Routine ordering becomes less important. Instead effort is refocused on directing the replenishment process, planning product assortment, defining product roles and service level goals, managing exceptions, as well as monitoring and developing the processes.
Often automation creates the right environment to push through broader changes in an organization. For example, many of our customers have moved responsibility for replenishment orders to a centralized team, which gives personnel at stores more time to focus on customer service and sales. Many wholesale companies have shifted away from a model where product managers are responsible for everything relating to their products, to one where a replenishment team is responsible for orders. This allows product managers to focus on product assortment decisions and marketing.
Change often breeds uncertainty, fear for one’s job, even outright resistance. Implementing change in good faith to create the lowest possible degree of resistance requires an investment in change management.
In any case, top-flight change management is needed to reach the goal. If old work routines and business models aren’t actively updated, there remains a risk that you’ll hang onto outmoded routines and won’t achieve the results you want. It is essential to set goals and metrics. If your goal is to increase sales by refocusing the store staff on customer service, it’s important to track the number of customer contacts and the average shopping cart size. If the goal is to make wholesale product replenishment more efficient, we can measure the proportion of approved order proposals.
The last challenge for change management sometimes comes as a bit of a surprise. When product replenishment targets, such as shelf availability, inventory value or loss, can be managed through a centralised system, clear target levels are needed. In companies where this had been done locally and manually, store and product managers were often given apparently contradictory priorities; achieving perfect shelf availability and low inventory levels. Accordingly they set replenishment order levels to what they thought best. With automated ordering someone has to set realistic target levels.
How Can the Pitfalls Be Avoided?
With years of experience, I believe that the two first challenges cannot completely be avoided, especially if replenishment ordering is initially performed manually. If it’s not being used in managing the replenishment process, product data is often not maintained very well. A decentralized assortment process is rarely the result of a systematic development process, or of teams working together.
For this reason one has to accept that getting master and assortment data up-to-date generally requires both time and resources at the outset. The more widely this data is used, the more quickly problems can be identified and fixed. This can cause a lot of frustration in the beginning. Therefore, it is essential to explain to your colleagues just why it’s so important to have accurate data, and that poor results arising from poor data isn’t a system problem or the shortcomings of a new operating model. At the same time you should consider how basic processes (for example, receiving shipments, inventory management or new products processes) can be structured to minimise errors. Most people want to do their job as well as possible. It’s management’s responsibility to create and maintain the right conditions for colleagues to succeed.
There are no short cuts to change management. So set the target levels, discuss them openly and listen. Setting internal target levels and maintaining a focus on them requires continuous effort. Nearly all of RELEX’s clients have said in retrospect that they should have invested more in change management. Don’t forget; with change management we’re not just trying to minimize problems, we’re also trying to generate and maintain enthusiasm. When you get your whole team working together on the development of a new operating model, the results will exceed your expectations!
We at RELEX have extensive experience in making forecast management more efficient in partnership with an impressive roster of companies. Together with our customers, we have successfully worked on sales planning and forecasting models as well as the use of quantitative forecasting models.
Take the first step towards better forecasting and contact us. An hour’s meeting is enough to go through your company’s situation and to define the first steps!
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