The recent report from Oracle presented data issues and information quality as being a key facilitator in lost business revenues and inefficiency (you can see the report here http://emeapressoffice.oracle.com/Press-Releases/Oracle-Research-Reveals-1bn-Cost-of-Fragmented-Supply-Chains-183a.aspx). The Oracle report, indicated that executives spent a significant time reviewing information, but over 30% suspected that physical products flowed better than the data within their organizations.
When you consider the sheer volume of data that is created and managed by a typical supply chain this is unsurprising. Consider the following data that most organizations will have within their systems
• Open Purchase Orders
• List of suppliers
• Price lists
• Parts Master
• Customer Lists
• Authority lists
• Material demand and requisitions
Now consider the impact of that data either being incorrect or slow to move from one place to the next. Whilst it’s a key business issue its one that is all too common.
Lets look at one example – the parts master. Typically controlled within the ERP system most parts master databases will consist of part numbers, descriptions, unit of measure etc. Where there are no robust processes providing controls it is not uncommon to find that
• Obsolete parts remain live within the database
• Part number syntax rules are not adhered to and the part appears multiple times in various guises (e.g. ABC123, ABC-123, abc1-23) resulting in confusion
• Free text is just that – consider – “Metallic clip”, “clip, metallic”, “clip”, or even the dreaded “-“ killing any hope of reliable management information.
• Associated data (e.g. unit of measure, Min/Max buy quantities) are incorrect or poorly maintained
• Etc etc etc
The impact of these errors and inconsistencies is that data that triggers decision making is poor (often resulting in the role strategic choice) and the processes that consume this data are inappropriately slow and cumbersome.
Many systems do not make managing data simple
One of the key issues especially within the supply chain is that there are often numerous (stand alone) systems at play which requires manual alignment of key datasets. For example, the procurement system and financial systems are often divorced but supplier data needs to be shared between them to maintain bought ledger requirements. I have lost count of how many times I have reviewed live supplier lists that include terms such as “Do not use” or contain multiple version of the same supplier with different spellings. Managing and maintaining isolated databases can be a key reason for poor data with companies often overlooking the benefits of system integration.
The result
But why is this important? Purchase orders still get sent, suppliers are still paid, inventory is still supplied. The true cost of poor data is efficiency and agility. Organizations that struggle on a daily basis with data are most likely both un-responsive and unaware of true performance (and therefore how they can improve). This does result in a cost to the business and at worst poor processes that are executed without true requirement.
In today’s highly competitive market this is not a problem that businesses can afford to live with. How do you solve it? Business must make data integrity and communication seriously it must become a key strategic objective. Resources must be appointed to ensure quality and the businesses must work with its supplier network improve data across the supply chain.