People are often a little cloudy over the difference between procurement and purchasing. Both strategic functions lead to expenditure spend, but the divide between them is not so difficult to delineate.
Procurement is generally agreed to be the first of these two strategically related actions. It is the process of researching, analyzing, assessing, auditing and evaluating a product or service before expenditure is released. Purchasing comes logically after procurement. It is the process of raising purchase orders, arranging finance and arranging payment for the products and services in hand.
Once we combine procurement and purchasing into one fluid action, we get spend. This in turn means that, logically, an accurate spend analysis process is one that extends as far back down the procurement and purchasing pipeline as possible.
Spend analysis mechanics
Once inside the mechanics of working operational spend analysis, we can see that actions include the collection, cleansing, classification and analysis of expenditure data. When we look at the spending being channeled to suppliers with an analytical eye, we can then work towards decreasing costs, improving efficiency, monitoring controls and compliance. We can also work better to predict future spend scenarios.
Spend analytics enables organizations to reduce the incidence of rogue or off-contract (or non-compliant) purchases carried out by individuals, teams or departments. It also enables companies to align their procurement plans with working dynamic changeable business demands.
As an organization becomes more adept at spend analysis, it can increase supplier value and performance to ultimately gain increased opportunities to make savings and maximize the Total Cost of Ownership (TCO) of all products and services. As firms use spend analysis tools to innovate internally, they can benefit from benchmarking their commodity management process to achieve more intelligent forecasting. The end result is a business that can engage in smarter strategic sourcing of all products and services.
A brief history of spend analytics
Real world spend analytics is now at the point where it needs to move to its 2.0 generation iteration. Early developments in this arena saw customers take spend data from Enterprise Resource Planning (ERP) systems and attempt to take what insights they could glean from this process to create an ongoing procurement and purchasing strategy.
Many of these now-archaic systems suffer from only being able to look at historical spend; they are not natively engineered to be able to predict future forecasts and/or dovetail with intelligent organizational workflow systems inside businesses that have progressed through several tiers of digital transformation.
These older systems were made it tough to import, cleanse and classify spend information, meaning that much of it had to be carried out manually using spreadsheets. The clunky processes of the past were often still known as so-called ‘solutions’, but they typically failed to deliver much in the way of spend execution, resolution or indeed revolution.
A new approach to spend analytics
Instead of depending on industrial spreadsheets, a contemporary software planning platform approach to spend analytics delivered through Anaplan provides a means to help procurement and finance professionals automate the process of analyzing spend data from transactional systems (including ERP + Procure to Pay (P2P)) to create future forecasts that better predict supplier spend and savings ideas.
The credibility of the organization often rests on the procurement function’s ability to responsibly articulate potential changes to spend with objective data. In response to this market need Anaplan and Vuealta created a new spend analysis model.
Moving forward, organization using modern spend analysis tools can look to rationalize their supplier relationships. By consolidating their spend actions, organizations can increase their buying power, achieve deeper discounts and work to get more value out of every spend translation carried out.
Forward-looking orrganizatons using these tools can also engage in value engineering and look for ways to work with suppliers to reduce their own internal costs. Using techniques including robotics or automation to lower manufacturing costs, firms can pass savings on to the customer base to increase maket share.
The future for spend analytics sees organizations adopt an increasingly connected and intelligent set of platform-level software tools to automate decision making, forecasting and ongoing analytics to perform better at every level. Spend analytics is, to coin a phrase, well worth the money.