Posted by  Charles Clark  Published on  27 Jan 2016
  • Procurement Strategy

Recently, we hosted a webinar on the topic on why procurement are establishing centers of analytics. By far, it was our best attended webinar, which reflects the growing interest in how to create value from data.

Back in 1990, Doug Laney, research vice president for Gartner Research, termed the name Infonomics which helps us determine a baseline value for data as well as how to measure the value of that data over time. It can help to put a value on data, turning what many considered for years to be just a by-product of business into a corporate asset. 

In one of Hugh’s first slides, he provided a macro overview of growth, inflation and commodity prices, all of which pointed to a more complex and tougher environment.  In his last slide, he left us with the traditional three factors of production: land, labour and capital BUT included data as the new fourth.  

Procurement leaders are familiar with the old adage, "you can't manage what you can't measure." They all appreciate the significance of data management and value of data governance, both of which lie at the foundation of Laney's infonomics and its applications such as spend analytics.

However, although it makes infinite sense to talk about data as an asset, we also need to treat it as one. Teams that make a point of valuing information enjoy higher levels of productivity, cost reduction and faster better decision making; teams looking to productize their data are innovating faster and developing new value streams.  Companies like Babcock and Sony are examples here of where teams have embraced a framework to usher in new levels of performance and productivity.

Accounting for data isn’t easy.  In fact, it is far easier to account for buildings and plants than information assets; but if we ask ourselves what (potentially or really) creates more value for the enterprise, we may be surprised by the answer. In fact, there is increasing evidence that businesses are starting to place a much higher premium on "information-centric" teams and enterprises.  

Elevating the importance of data will almost certainly lead to higher levels of innovation which will impact a team’s culture, whilst shifting the perception of the department by the c-suite. One of the most important things about data and information is that it creates a common language between procurement, operations, finance and IT.

Another way to possibly look at this is to consider the difference of being told you are in charge of the vendor masterfile versus you’re managing a $1 billion information asset. Placing pound or dollars signs on data to create a common language across the enterprise is an intriguing idea.

Here are five models used to measure the value of data (Source: Doug Laney, Gartner):

Non-financial methods

1. Intrinsic value of information. This model focuses on the spend data's intrinsic value not the business value. The model quantifies spend data quality by breaking it into characteristics such as accuracy, accessibility and completeness. Each characteristic is rated and then tallied for a final score. Spend data that is unique to the enterprise and not available to others has a higher value.  

2. Business value of information. This model measures spend data characteristics in relation to one or more business processes i.e. spend analysis. Accuracy and completeness, for example, are evaluated, as is timeliness. The model can be customised to the teams needs and even applied to specific spend data types such as unstructured data (PO line item description) or third-party data (Parent child relationships).

3. Performance value of information. This model is more practical as it measures the spend data's impact on one or more key performance indicators (KPIs) over time.  Take the procurement department, for example, if the team were to reduce their sourcing cycles by 10%, how many more events would they be able to complete in a year and therefore potentially save more money. The team could run a test by comparing how a group with no access to spend analysis performs against a group who has access to the data and analytical tools.

Financial methods

4. Cost value of information. This model measures the cost of acquiring or replacing lost information.  This is an accounting driven exercise and for a procurement team would focus on calculating the opportunity cost of missed savings plus the cost of acquiring the data again. 

5. Economic value of information. This model measures how a procurement teams information asset contributes to the savings of the enterprise.  Procurement teams should factor in the cost it takes to acquire, administer and fully integrate that data into the systems the team are using. They should also consider the data's life span. Spend data has a shelf life which should be factored into its value.