Action !

One of the key outcomes of any analysis training is in the creation of an action plan.   The programme will focus on packaging and presenting ideas for action to deliver the right results.

To make data work we have to make connections

Most manufacturing companies have parts and materials ordering well managed...but indirect spend ?   However, from our experience, even purchase orders can be wrong.   A myriad of mistakes can be made with pricing, contracts and data.   It pays to check.

Effective spend analysis requires connections in the data.    There are two key connections.  The first is in linking all of the same name vendors together - this helps eliminate multiple entries for the same supplier.   The second is in connecting often vague general ledger codes to more readily understood purchasing categories.   For example, purchased services could contain spend on print, temporary labour or trades-person spend.    This process makes the spend easier to understand and interpret.    We get you to focus on using data from whatever source you can obtain it.


The business world is obsessed with reporting.  However, isn't the objective to use the data for insight?  Savings?  Efficiencies?

Once the data has been structured and is coherent, analysis and reporting can commence.   Creating quality reports and insight are key elements to successful spend or cost analysis.


All spend data is contextual.   However, the combination of data, spend intelligence and organisational context enables a well trained spend analyst to seek and deliver commercially focused outcomes.

A wide range of data..

Almost all organisations seeking to save money or improve their purchasing capability need to understand their data.   To leverage spend data and improve procure to pay efficiency(P2P)key data sources need to be identified and understood - invoices, purchase orders, corporate or purchasing card data all need to be managed in to a usable structure.   However, even if you are a basic Excel user, there is much you can do with the data.   You have to start somewhere.