How do I export data from my finance system?

You can normally run reports on your finance system to export, Suppliers, Purchase orders, Invoices, catalogues and contracts.

We do not know how to export data from our finance system. Can you help?

cloudBuy can take the data directly from the underlying database that your finance system is based upon. You will need access to the underlying database.

We already have the information in Excel spreadsheets, can you use that?

cloudBuy can use your Excel spreadsheets. However, it is possible that the data has been corrupted in the process of transfer from your underlying systems to the Excel spreadsheets, especially in Excel 2003 and earlier. Issues also arise when the Excel spreadsheets were not a direct export from your finance system. This is why cloudBuy prefer a direct export from your finance system.

Are there any limitations on the data analysis?

Yes, we can not analyse when there is no data! For example, if a purchase order line simply says ‘see quote 12056’ then a human, let alone a computer, cannot tell what is being bought. When this only occurs infrequently it need not hamper the overall analysis.

How accurate is the data analysis?

SpendInsight is for procurement, not finance. We are interested in identifying those products where the expertise of a procurement professional will be most gainfully employed, and empowering them with the data they need to affect change. Therefore identifying savings at line item level is more important than accurate overall statistics.

Because SpendInsight works at the line item level, you can always drill down right back to the original purchase orders to substantiate for yourself any claims being made about savings.

The automatic classification to eClass or NSV is generally better than manual classification that has been carried out in assigning spend into categories within the finance system. However, the data analysis is not 100% accurate, in terms of auto classification and matching.

What is the data coverage?

Everything! Well, 100% coverage of the data supplied at line item level. This is a significant improvement over previous methods that provide partial coverage at category level, but then drilling down from categories to items is left as a manual process.

How big are the potential savings?

It depends on the organisation, but it is not uncommon to see savings of 6% to 12% on affected spend. This is just what the system is confident in; the data pack can showall possible savings, which includes false-positives but may highlight even more opportunities.

How do I get from a data pack to making savings?

This is the hard part that a computer can’t do. (Maybe it can, actually.)

There are two ways of realising savings – by improving processes, and by improving purchase price. Both are significant, even for the best organisations, because it is impossible to purchase every item at best price all of the time.

There are always areas for improvement on purchase price, and an understanding of how well you are purchasing. Very few organisations have 100% compliance with purchasing process, and the maverick spend is often purchased at list price which may be 50% above contract price, and even the best organisations have free text orders going out with uncontrolled pricing.