For any enterprise, the ability to accurately analyse their spending can be enormously beneficial. Not only can spend analysis assist with identifying potential areas for reducing cost, it can also help to improve operational performance, as well as assisting with compliance objectives.
However, many organisations remain unable to perform effective spend analysis due to a lack of sufficient, accurate and timely insight into corporate spending.
Access to carefully consolidated data is essential in helping enterprises to understand their spending patterns. This in turn is critical for optimising spend and leveraging maximum value from budgets to boost the bottom line and enhance performance.
Spend analysis can be defined as the process of aggregating, classifying, and leveraging spend data for the purpose of reducing costs, improving operational performance, and ensuring compliance. With this definition in mind, spend analysis should include: the identification; automated collection; cleansing; grouping; categorisation; and analysis of all spend data for the goods and services purchased for the organisation.
Utilising and analysing spend data can help enterprises to understand what was bought, when and where, how many suppliers were used, how much was spent with each, how much was paid for the items, and more. With this information at their fingertips, organisations can identify and focus on items that have a disproportionally high spend. Utilising root cause analysis may then identify a more cost effective solution, or allow a discount to be negotiated with a supplier. Spend analysis can be highly beneficial to assist procurement organisations with leveraging buying power, reducing costs, better managing and overseeing suppliers, and developing an informed procurement strategy.
While the concept of spend analysis seems straightforward enough in theory and the benefits are clear, in practice they may prove difficult to achieve, as a result of a lack of appropriate data. A number of factors may affect this, including poor quality materials, services and supplier data, with the result that the total spend on a particular item, or supplier, may be impossible to identify. Some other challenges surrounding data for spend analysis purposes include disparate data sources, inconsistencies with vendor or supplier naming conventions, inaccurate or incomplete procurement data, limited analytics capabilities, and the use of manual spreadsheets for the classification and analysis of data. Without adequate and accurate data, organisations are typically unable to realise economies of scale or gain a comprehensive view of business spending.
Data quality and data governance are the keys to unlocking the potential of spend analysis, since it is dependent on the accuracy and consistency of materials and services data captured during the procurement process. For example, when the same item is captured more than once, with varying descriptions or units of measure, the spend analysis will typically recognise these as two separate items and does not reflect an accurate total spend. Minimum product standards need to be agreed upon and enforced through a combination of education and data quality rules and validations. This creates the accurate “single view of the product” that is necessary for meaningful spend analysis.
Gary Allemann is the Managing Director at Master Data Management.