How to achieve acceptance
In recent years, more and more companies have turned to automated planning processes in the areas of supply chain management and materials management. Automation of planning processes refers to the use of algorithms and artificial intelligence (AI) to automatically generate forecasts for future sales figures and subsequently plan material and resource requirements in an automated manner.
For manufacturing and retail companies, automating planning processes is critical for several reasons. First, it enables a significant increase in productivity. Automation reduces manual tasks, eliminates errors and frees up time for strategic decision-making. Furthermore, it is a solution to the growing problem of skills shortages caused by demographic trends. Our societies are ageing, making it increasingly difficult to find and retain qualified personnel.
Acceptance of automation often fails for eight main reasons
User acceptance of automated planning processes can of course only be expected if the forecasting and scheduling system is able to deliver reasonable results. In practice, this is seldom the case, unless one has worked intensively on optimising the planning parameters and has tested the resilience of the setting through simulation.
But even where we have created these preconditions in our consulting projects, we encounter reservations about the implementation of automated planning processes among users. We often come across these eight main reasons for the lack of acceptance:
- Lack of understanding of how automation works: many employees do not understand how algorithms work and therefore have little trust in them.
- Fear of job loss: Employees fear that automation will make their jobs redundant.
- Fear of mistakes: Some employees fear mistakes made by automated systems that they cannot notice or correct.
- Uncertainty about technology: There is a general uncertainty about new technologies and changes.
- Need for control: staff want to be in control and therefore prefer to manage forecasts and orders themselves.
- Skepticism about “black box” decisions: Decisions are made in a “black box” – not comprehensible to staff.
- Lack of trust in the accuracy of forecasts and replenishment proposals: Especially long-term employees are convinced that their intuition and experience often lead to better forecasts than algorithms.
- Lack of adequate training and support: Many employees feel overwhelmed with the new systems and not sufficiently supported.
The “classic” measures for more acceptance only help in part
In order to overcome the reservations of the employees and to bring them along, the “classic” measures are cited again and again. I have had good experience with a complementary pragmatic approach. But first let’s take a look at the classic measures:
- Education and training: when employees understand how the systems work, their confidence in the new technology often grows.
- Clear communication about the benefits of automation: If the benefits of automation are openly discussed, this sometimes helps a bit. Automation is more likely to be accepted especially when the employees concerned are overworked and automation does not replace jobs but improves them.
- Tolerant handling of errors: A tolerant handling of operating and decision errors can also help to increase user acceptance and reduce fear of the new solution.
- Involving employees: At least some of the employees can identify better with the new automated planning processes if they are actively involved in designing the automated processes.
- Create transparency: If you can make it comprehensible to users how a supposed “black box” decision comes about, this transparency also promotes a bit of trust in and acceptance of the systems.
- Demonstrating the resilience of forecasts and scheduling proposals: If it can be shown on the basis of simulations of past values that the automated forecasts and scheduling proposals have not performed worse than the users’, this promotes acceptance considerably among technology-enthusiastic superiors. However, many users, especially long-standing ones (to avoid the term “experienced”) often feel attacked by this.
Pick up skeptical employees through automation buffers
My additional suggestion: try an “automation buffer“.
In day-to-day business, users are regularly faced with the dilemma of having to plan material in such a way that the required product availability is achieved and yet stocks are kept as low as possible. Too much stock leads to stress just as much as too little product availability of a material. A lack of material usually causes more stress than too much stock. Missing material interferes with operational processes more than too much stock, production cries out, sales duns and sometimes management even gets in touch. When I ask the users why they want to check the scheduling proposals from the planning system and not implement them unseen, I usually hear the fear of missing material, less often the fear of too much stock.
In such cases, I propose a small deal to the users, which we initially agree on for just a few pilot items as a test. I negotiate an additional stock that we allow for the material. This stock is to ensure that sufficient product availability is available even in the case of faulty material planning: depending on how the planning solution is designed, this “automation buffer” can be realised in different ways. In the DISKOVER system, for example, one can define a minimum stock level that is never fallen short of, even if DISKOVER thinks it can manage with a safety stock level below the minimum stock level. Another possibility is to define a manual safety stock factor with which one can further increase the safety stock determined by the system.
Step by step, create more confidence in automation
My experience shows that if the users get involved in this deal and we agree on an automation buffer, then they also give the automated planning of these items a chance. After a few weeks, I look at the replenishment situation of the items again together with the planners. Usually, we then realise that the automation buffer was never or almost never attacked, so we can agree to turn the automation buffer down a bit. After a few rounds of optimisation, it is possible to reduce at least a large part of the automation buffer in this way. An essential prerequisite for this is, of course, that the system’s scheduling proposals are correct, i.e., that the scheduling is set up properly.
If the pilot application was successful, we roll out the automation buffer to further items and thus continuously increase the degree of automation. In this way, it also becomes clear where the automation of the disposition is not yet effective, where it is therefore better for humans to intervene and where disposition rules and regulations need to be further refined.
A significant side effect: avoiding misadjustments of planning and scheduling parameters
The turn with the automation buffer offers another significant advantage. Users no longer feel compelled to hide inventory securities in different places in the planning system. Even if users have little knowledge of the planning algorithms in the software, many quickly find out how to achieve a higher inventory level, regardless of the set level of delivery readiness, by changing opening horizons, through manual safety stocks, increased goods receipt processing times, lead times in the system and other tricks, . In this way, disposition parameters that have been set cleanly with a lot of effort are lost again if it is not possible to ensure in a differentiated way, as with DISKOVER, via planning rules and regulations, that the parameters are set cleanly and are reliably adhered to.
Better to face the inevitable
The productivity of our companies depends on the automation of business processes and thus also on the automation of planning processes. Due to demographic facts, there is no way around this. It is better to take the employees with us on the path of automation today than to find out tomorrow that we will be without employees and without properly working processes!
Image: © by iStock