{"id":20015,"date":"2021-02-18T11:12:00","date_gmt":"2021-02-18T10:12:00","guid":{"rendered":"https:\/\/test.encoway.de\/cost-drivers-in-product-data-maintenance\/"},"modified":"2024-11-28T13:45:22","modified_gmt":"2024-11-28T12:45:22","slug":"cost-drivers-in-product-data-maintenance","status":"publish","type":"post","link":"https:\/\/www.encoway.de\/en\/blog\/cost-drivers-in-product-data-maintenance\/","title":{"rendered":"How to eliminate the cost drivers in product data maintenance"},"content":{"rendered":"\t\t
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... and achieve a real competitive advantage through efficient data maintenance<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Product data maintenance is time-consuming and costly. Its optimisation is a tiresome topic that no one is particularly fond of in a company. This is something we want to change! With our \u201cPotential analysis – cost drivers in product data maintenance<\/strong>\u201d we will work together with you to identify the causes and to make concrete recommendations for improvement. In this way, you will be able to avoid unnecessary costs in the future and establish a sustainable basis for your product data maintenance. <\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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The statement \u201cProduct data maintenance is time-consuming and costly\u201d was confirmed by 74% of the participants (!) during the \u201cProduct Management Study<\/a>\u201c. Of the many other challenges mentioned, this problem was given the strongest weighting. Of the many other challenges mentioned, this problem was given the strongest weighting.<\/p>\n

For us, this was a good reason to get to the bottom of what causes this and to identify possible solutions for companies.<\/p>\n

The challenges<\/h2>\n

Important but unpopular<\/h3>\n

High-quality and highly available product data is immensely important, especially in the age of digitisation \u2013 you cannot hope to achieve effective digitisation without a good database! Despite this, we have often seen that product data maintenance is regarded as a necessary evil. One product manager at a major appliance manufacturer said:<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\u201cCreating an item in our MDM system requires a lot of work; we have to maintain the fields page by page.\u201d<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Why is product data maintenance so unpopular \u2013 both with the data maintainers themselves and with those who provide the funds for possible improvement projects? The phrase \u201cconsiderable effort\u201d mainly refers to monotonous manual activities. Most people find repetitive tasks tedious and dislike doing them simply for that reason. One product manager of a medium-sized machinery manufacturer said:<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\u201dWe have a great deal of redundant data maintenance because the tools are not interlinked with each other.\u201d<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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And then there is the lack of transparency regarding what happens to the data. If data maintenance knew right at the beginning of the process chain what was needed for the subsequent use of the data and why, the motivation to provide good data would be quite different. A lack of consistency can have disastrous consequences, as the example of another product manager at a large component manufacturer illustrates:<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\u201cNow that we know the huge amount of data maintenance that a product modification entails, we often ask ourselves whether we really want to implement it at all. Sometimes we are even willing to live with a lower-quality design in order to avoid the excessive data maintenance.\u201d<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Who will pay for it? No budget for better data maintenance<\/h3>\n

The willingness to invest in improved product data maintenance is relatively low, even at C-level. Often, data maintenance is generally seen as a cost driver. Additional staff are rarely made available if the costs exceed those that are \u201calready there\u201d. <\/p>\n

It is indeed true that a return on investment (ROI) for the optimisation of product data maintenance is very difficult to calculate. This is mainly due to the fact that the costs of data maintenance and the benefits it generates are incurred at different points in the value chain \u2013 i.e. in different departments within the company. This makes it difficult to explain why investments should be made in one\u2019s own cost centre, where only a \u201cminor\u201d sub-benefit is generated. <\/p>\n

If the investment has to be allocated among different cost centres, it will become too complicated for many of those responsible and nothing will happen.<\/p>\n

New requirements \u2013 old data<\/h3>\n

New requirements, such as standardised data exchange formats and the introduction of new IT systems, require a suitable data basis:<\/p>\n