Maximise Your Data

Commercial Data Cleansing

• We separate this broadly into 3 camps. Obsolete, Erroneous and Sub-optimised. The first 2 can often be tackled in isolation. However, sub-optimised data is more subjective. Are we charging the ‘right’ price or giving the ‘appropriate’ discount to this customer for this product? Do we need to change associated parameters taking into account external factors such as product life-cycle, seasonality or competitive situations?
• Changes in data due to changes in circumstances in one department can render other commercial elements ‘sub-optimised’.
• MYD have developed a wide range of master data audit and correction routines and can advise on the cleansing of Obsolete, Erroneous and Sub-optimised data.
• Because we take a total integrated view of the commercial data, we understand the interactions between data that may be being maintained in different departments within your organisation.

If you are a large wholesaler that manages a large proportion of your business by applying discounts to groups of products from a trade price, then we would expect you to have many millions of resulting customer prices set to make a negative margin. You probably don’t even realise it!  

• Some of the variation in available margin within these groupings can be vast, particularly with certain manufacturers.
• Maybe you have negotiated a keen purchase price on a product or range of products. The sales team may want to offer a good deal to their customers so set a higher discount. But what about all of the other parts in this group that now attract the high discount? Are you throwing margin away on these? Have these parts now been indirectly set to make a low or even negative margin?
• Many of these combinations will probably not sell – But how many do sell?

Do your staff detect the low margin sales that are set up in your systems and override the price upwards? In our experience, this opportunity is likely to be huge.   

Complex corporate customers

• Some corporate customers have complex hierarchical structures, and can often have prices, discounts and deals pitched at different levels in the structure. This can be an excellent place for profit to hide.
• Deals at different organisational levels can override other deals that were thought to be in effect. This can result in not only lost margin, but in invoice queries where the customer believes that they have been overcharged. Unfortunately the customer rarely complains about being undercharged!
• Are there old obsolete accounts still in place in these structures? Are sales being made against them with obsolete pricing data?
• A thorough Customer Data and Structure review can reduce complexity, aid understanding and release hidden profit. (See Case Study 2)   

MYD can review all of the data related factors that are causing profit leakage. Re-aligning your databases can return a very significant profit improvement .

 

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