IBP for MRO – of course it’s all about the Forecast!
I had the chance last night to speak with an IBP customer starting a deployment to manage MRO for a set of mobile and fixed assets. While nothing I say here is confidential, I will respect their privacy as i did not request permission to “name names”. But they are of course free to provide an identifying comment.
We talked about a broad range of topics impacting planning for MRO, they are well informed and have been in contact with SAP executives in both IBP and Asset Management domains. They have some great ideas on Internet of Things and predictive maintenance processes, and a well thought out model for managing execution.
But in maintenance, managing execution doesn’t matter if the right part is not in the right place at the right time. A failure of the supply chain to have parts available impacts throughput via asset downtime, and loss of maintenance technician time spent searching or waiting for parts.
Looks like a process where IBP can complement SAP’s other execution tools, and it is.
The big question we debated last evening is “what is the most important planning tool – Supply or Inventory”. Sorry, there is no one answer. I was educated in economics, so will fall back on “It depends..”
What it depends on is knowable, though, and that’s forecast quality. I doubt there would be any argument that the better your preventive and predictive maintenance planning process, the better your forecasts of required service parts will be. Read this as leading or bleeding edge incorporation of big data from IOT sensors mated to other explanatory variables predicting not only moment of failure but likely parts required.
Parts required? Yep… as we discussed, an asset-intensive company probably has a good grasp of the maintenance parts that are always required for a job, and can explode from a job forecast easily. It’s the sometimes required items that are a “gotcha”. Big data and predictive analytics can help here too.
So it’s not inconceivable that at some point the enterprise will develop a forecast of MRO items that is sufficiently accurate to enable planning with static, periodically evaluated safety stock levels and a combination of IBP Supply and MRP reorder point and safety stock.
But my contention is that is not true now, at least not for the vast majority of MRO companies. The fact that we had a discussion last night verifies that it’s not true for my new friends.
That’s where IBP Inventory comes in. Applying the tools of a multi-echelon inventory optimization that embraces forecast variability and supply chain nodes and lead times to manage materials at central and on site facilities enables strategic management of inventory buffers and working capital simultaneously. My contacts last evening even recast the “customer service level” we think about in Inventory Optimization into “uptime target”, with the “customer” being a piece of equipment using the part. That’s cool, and is easily enough done with the IBP structure.
SAP believes this strongly enough that our Inventory solutions management team has created a standard demonstration model of the MRO case, and used a similar construct – “customer” master data represent unique equipment objects, aircraft in the case of the demo. It’s a joy when great minds think alike – not me, our customer and our Inventory team.
One last thought to close, which we also kicked around. A technique I like to suggest whenever a material has attach rate demand (which is a valid assumption in maintenance planning) is to generate a forecast based on explosion of the relevant parent item. But also generate a univariate, or maybe even univariate and regression, forecast of the material as well. Any significant difference suggests an opportunity for analysis and improvement.
So MRO professionals, either in an environment where your domain is the primary materials planning focus, or only an important part of a company where other materials planning challenges predominate, take a good hard look at how IBP can improve you forecast, inventory and overall performance