In a different life, I worked as the PMO for a global SAP deployment program at a large industrial company. As we work with customers of MachIQ Seva, who are approaching plant operators with digital services offers that they deliver on our Asset Performance Management software, I have a sense of deja vu. The underlying challenges that hold-up ERP deployments are the same ones that deliver sub-optimal results in digital plant projects as well. In this article I share the lessons I learnt back then that are still valid today.
Optimising sales for the wrong persona
Most decision makers for software purchases are “managers”. The sales arguments are always all about how decision support information will be delivered at the click of a button. Any sales demo has to have an “analytics dashboard” with cooked data that helps managers imagine how beautiful their life will become once the software has been deployed. What is usually less apparent is the amount of data entry effort that this translates for the people on the shop-floor. Naturally, when the software is being deployed the users push back, the training sessions are chaotic and the typical result is that users do the bare minimum that the newly defined process requires of them. Most of those beautiful graphs remain empty or worse, inaccurate.
The lesson we learnt: Bring in the intended users whose data entry will power the software into the decision making process early in the purchasing/sales process. Hear them out and ensure that there is enough meat on the bone for them as well. If the software can automate some of their most painful tasks, you will have buy-in and their enthusiastic preparation could mean that the project may even be completed ahead of schedule.
Putting junior project managers in charge
Managers often think that digital is something fundamentally new and that mid/senior level employees are completely incapable of understanding the benefits. Many customers we talk to like to put younger, high-potential employees in charge of deploying these new technologies in the plant. These managers have a limited understanding of the legacy of the plant and the background of why many of the processes were put in place, irrespective of whether the processes are perfect or painful. And I speak of a younger self when I say that younger project managers tend to be idealistic instead of pragmatic and are often unaware of the downstream human costs of deploying certain technologies. The most common result of this is best summarised below – the project might be completed, but it won’t deliver the expected benefits.
While younger employees master the technology, it is unreasonable to expect them to determine the full value of- and anticipate the obstacles to- such technology. When some projects eventually do succeed, it is almost never without a lot of rethink and additional reinforcement in change management.
The lesson we learnt: Appointing more senior profiles as project manager, able to bridge the business needs with the capabilities of the technology is critical. Also, change management involves a lot of stakeholder management and convincing people with very different interests. Further, the big picture perspective that more senior employees have enables them to look beyond pilots and tests. A technology pilot deployed on a small sub-section of a plant and might appear to be successful but if there is no scale-up potential for the technology to benefit a big cross-section of the plant and its employees, eventually the business case for such a technology will be poor. Prior business experience is a more critical success factor than technology savviness.
Data is destiny
This is common knowledge now, but even so, data is the least favourite topic of employees at all levels. No one wants to work on data cleansing and everyone wants to “outsource” the task to suppliers/consultants. The problem with this is data is business and external consultants or interns or junior employees don’t quite understand the business like experienced employees do.
The lesson we learnt: This is often where appointing young high potentials is a great strategy (we are hiring young high potentials by the way). Working on data offers them an accelerated path to understanding the company’s operational priorities and the strategy on the whole – enabling them to prioritise the data that needs to be treated. It also filters out high potentials who have great profiles but are simply unwilling or lack the stamina to roll up their sleeves to get difficult work done.