Getting Data Right is a Critical Commercial Issue for Manufacturing Businesses
We meet many manufacturing CEOs who are frustrated that, despite spending huge sums on new systems, they are still unable to get visibility of the true cost of production, have higher than expected waste and no clear view of inventory on hand or on-order.
New systems like IFS, Nav, AX or Dynamics 365, SAP, Sage, Epicor, Oracle or Syspro can cost huge sums, but if the project fails to deliver often the root cause is that the master data in the system is wrong. For example product costings, Bill of Materials, Recipes, routings, etc may have not been setup correctly in the first place or may have become out of date. The tech may be fine (though often it isn’t!) but if the data is wrong then everything else is “built on sand”.
Poorly controlled master data confuses everything – same customers, FG’s (finished goods) or RM’s (raw materials) entered multiple times but called different things. And the bigger and more distributed the company, the more this can happen. Reports are wrong or time-consuming to fix; customers are upset by incorrect, incomplete or late delivery; procurement over-order to create safety stocks; sales can’t accurately forecast delivery dates; labels or documents may be wrong which can be inconvenient or, more seriously, can have legal or safety implications.
Fundamentally, poor data can make it hard to take advantage of efficiencies of scale. New systems are rolled out but problems remain and a growing business becomes less profitable rather than more profitable.
What are the root causes and real solutions?
1. Strong leadership or ownership.
Data is difficult, detailed and, let’s be honest, it’s not very interesting. Solution vendors are contracted to deliver some tech, so they don’t really care. Everyone’s too busy doing their day job so it may get left to the Finance or IT teams to sort it out, and they may not have the knowledge to fix issues or the authority to get people to change bad habits?
This issue has strategic implications so a Board-level leader needs to take ownership. The individual needs to have time to get to the bottom of the issues, experience of this kind of work, and authority to make decisions and get things done.
2. A complete strategy and solution.
Data problems often reflect process problems, or lack of alignment between people and departments. It may not be clear internally who is responsible for what, for updating data as things change, for correcting data if errors are found. Perhaps this kind of thing falls to some very over-stretched helpful people – and Directors wonder what they’re doing all day. There may be no-one who has time to get to the bottom of what goes on and why.
Sales, finance and production teams’ reports simply won’t agree if they are working from different base information, but they may have good reason for this and fixing the problem may require process changes, technology changes and some retraining (or even “redeployment” if the real issue is particular people!)
We often see data issues resulting from multiple systems being used but there may be good reasons for this. For example, specialist warehouse management solutions are often used as they integrate with advanced technology such as voice or sight picking which isn’t supported by basic ERP platform. But if you have separate systems there needs to be clarity around as to which system owns what data (eg ERP owns stock quantities, WHM owns stock location) and interfaces need to be complete, tested and working.
Overall the architecture of the processes, systems, and data needs to be clear, simple, well structured and then well implemented. Processes and data standard need to be defined and enforced. These activities need to be monitored and corrected when necessary.
3. Long-termism and commercial realism!
Data issues often arise because lack of time and commercial pressures mean that shortcuts are necessary. Getting data right may be a matter of diminishing returns as obscure problems can be very difficult and time-consuming to fix, and they may just not worth it!
The most important thing is to make considered and rational decisions. List the data problems, estimate the necessary effort for each, and the business impact. If short-term pressures mean that a problem won’t be fixed now, then perhaps it’s on the list for next month. The impact of these data problems can be monitored and, when time allows, further progress can be made.
Deciding to tolerate a problem for now is not the same as ignoring it or sweeping it under the carpet!
Even poor systems can work effectively if the data is well structured, well maintained and well policed. And, most importantly, this is a good platform for system improvements. Well structured data can eliminate a whole range of problems and inefficiencies, can boost profitability and give everyone new energy as less time is wasted on distractions and snags.
You may also like to read the additional content on our Manufacturing series:
Freeman Clarke is the UK’s largest and most experienced team of IT leaders and we frequently work with manufacturing clients to help them deliver transformational programs of improvement and system efficiency. We are entirely independent of any technology or suppliers.
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