Master Your Master Data
In almost every supply chain project weve been involved in it has been necessary to improve master data. Its almost a cliché these days but any system is only as good as the data you put into it.
Its almost a cliché these days but any system is only as good as the data you put into it. As they say, a perfect analysis of useless data is a perfectly useless piece of analysis.
You'll find the original post here: Master Your Master Data
When we sit down with new customers one of the first things we hear is almost always; our company has quite a lot of problems with its data so this might be a challenge
So, if that sounds like you, and youre considering implementing a SCM solution, you might well be thinking Oh no, my master data is completely inadequate. Whats the point?
Well, for starters, be reassured, youre not alone. Far from it. Almost every company weve worked with has had some challenges with its data. Is there a single company in the world that has no issues at all with its master or transaction data? Weve yet to encounter it.
At the outset having clear goals is much more important than having perfect data. Equally important is being sufficiently flexible that youre able to make changes and adapt on the fly. Dont expect to have everything in perfect shape before you start because it will never be perfect. As they say; the best is the enemy of the good.
Data issues are often completely understandable. For instance, if you have a system that isnt capable of factoring weather into demand forecasts then why would you bother to make a note of it? By the same token if your colleagues are recording data you dont use, consider asking them to focus instead on improving the maintenance of data that you do use or that you might anticipate using.
Quite often, when were working with a new or a prospective customer, we carry out an analysis of their operations and run their existing data through our systems (prior to their being configured precisely to the requirements of that business) which gives a good indication of the impact the latest SCM software will have on their operations.
One thing that routinely becomes clearer at this early stage as a result is where a company has good data and where it needs to be improved. As the quality of data will become critical when the implementation begins in earnest with the pilot phase, most companies start working immediately on cleansing and organizing their data.
However, at this stage most businesses only have a broad idea of where the challenges will come from. And, as a rule, as the implementation of a new system progresses, more and more data issues typically come to light. So most companies weve worked with simply accept that improving master data will be an ongoing process throughout the implementation and beyond.
With accurate sales data, data that can be broken down day by day, store by store, product by product, you can build up a good picture of likely demand. And if you realize you havent tracked all the data you now wish you had the good news is that with time you will accumulate the information you need.
If sales is one side of the equation, the other is inventory. In aiming to master your master data its useful to keep uppermost in ones mind the basic principle that unless you know what youve got its really difficult to judge what you should order. Its critical for an efficient replenishment operation is to have more-or-less up to date and accurate inventory balance data or stock balance data. That is an ongoing task and often means attention needs to be paid to operations and processes as well as systems. Nail these two and youre well on your way to mastering your master data.
OTHER DATA ISSUES
We typically spend some time during the implementation process considering how to handle the open purchase orders; goods that are on their way to stores.
For example, how do you handle an open order that was supposed to come one week ago? Do we treat it as though its coming or should we treat it as though its not coming anymore? Its about defining rules and deciding how to interpret the data in these circumstances.
But one needs to go further and think of data more holistically. Its one thing to keep on top of all the internal data generated by POS systems, stock control and so forth. But more companies need to be equally assiduous about external data supplier business terms (such as freight-free or full truck), offers, discounts and so forth. If that data isnt up to date, then it will affect the quality of the decisions made when using it. Someone needs to be responsible for ensuring that data management doesnt stop at the boundaries of your business.
You'll find the original post here: Master Your Master Data