An article for the Supply Chain Magazine, by André Vriens
Last week I was at a conference; supply chain professionals from all over Europe wondered how predictive analytics could further help optimizing supply chains. The question sounds good and lends itself for useful reflections on machine learning and artificial intelligence. Many companies see the possibilities and some are already working on attractive pilots.
At the same time, one key question arose in the first discussions, ‘what does this mean for our people and for us as managers and employers?’ Do we perhaps need other profiles? Should we deal differently with recruitment and training?
Due to increasingly dynamic markets and more complex integrated supply chains, many companies have in recent years simply adjusted their requirements with respect to personnel in, for example, planning and forecasting; many require higher than normal academic qualifications for positions than normal, in other words “we buy talent” as an HR tactic.
In less favorable economic times, this is not such a strange tactic. It’s logical under cost pressure to put as many different roles as possible into one single function. Consequently, everyone must be able to think integrally, have business and financial affinity, be analytical and system savvy and last but not least be a super communicator and team player who can think in integral processes. And so the equivalent of the sheep with five legs was born, the super beast that gives both milk and eggs and also produces wool and meat, or in German the “Eierlegendewolmilchsau”.
Can 1 person do everything? Different skills for different roles
From my practice as a consultant I am often confronted with the question, whether the planner of the future should not be a data scientist? Yesterday a planning manager told me “I’m afraid my forecasters hardly add value to the simple statistics in my APS. What now?”
Many planners see it as their job to change the planning. And research shows that more than 80% of all changes are small and often do not improve the forecast or planning. In addition, the more experienced group of planners seems to be happy to go home only if they have dealt with two emergencies during the day or have run to the aid of at least one customer. To change something in the plan sometimes seems to be a goal in itself.
The question to what is the essence of a role can’t be answered in one go. The first step is clear: start looking at the real added value and purpose of planning and forecasting from your total business. Only then apply the ‘who knows better than the machine’ principle. Based on this, first processes and then roles can be defined.
In practice, we see that more and more companies make a distinction in forecasting (for example a local demand manager and a central forecaster role) but also differentiate on the skill level (a master planner and scheduler of a factory need different communication skills). For the advanced among us: the roles of data engineer, data scientist, and business analyst are also fundamentally different.
Right person in the right place – Focus on skill development and enjoy the journey
Accepting that someone who has been stuck in the same role for 30 years and does not continue to develop is not justified and is undesirable. At the same time, however, we don’t want to have to continuously train new people, as with our commercial colleagues where moving to a new job within two years has become the norm.
We must realize that applicants asking the question, “what can you do for my development?” are becoming the new standard. With the improving economy and the ‘war on talent’ in the job market, we will have to start thinking differently. We must be realistic about what we can expect from a role and at the same time be more prepared to coach, guide, and grow people in their functions.
In summary, it has become necessary to not just offer a job, but also to develop in terms of knowledge and competences, both young professionals and ‘experienced hands’. No more fixed profiles, but an organic and learning organization. Good for the employee, good for the company, and if we do it right: we add real value ourselves!