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Spend Analysis Requires Human Expertise for Data Optimization, Data Visualization

From recent conversations during this fall conference season, it’s clear many procurement teams are still struggling with poor-quality spend data. Combined with the challenges of data lakes, corporate changes from mergers and acquisitions, and an overall pressure to get more savings year over year, procurement leaders are finding it difficult to align their talent and technology strategies for their digital transformation efforts.

Challenge of Spend Data with Suites  

To solve spend data and visibility challenges, many organizations are implementing procurement suite solutions. However, months and sometimes years into the implementation, some are finding themselves in the same position they started in, struggling to obtain data accuracy and spend visibility, while also lacking the internal expertise they need for building data-driven procurement strategies.

A recent conversation with a VP of procurement demonstrated this challenge quite clearly.  The VP shared with me that they chose a procurement suite solution, and have been trying to implement it for years. Overall, they have found it difficult to get all the modules from source-to-pay to work together as they expected. Moreover, after deploying the solution, the expectation was to get better visibility with one tool. While they have much of the data captured that they need for spend analysis, years later they are reluctant to accept the reliability of this data.

And while their solution vendor provides a service to consolidate and normalize their data into a spend cube as part of its offering, the VP and her team have questioned the data accuracy coming out of the spend analysis tool. Thus, they’ve had to delay further opportunity assessments because they simply don’t feel confident executing sourcing strategies against the spend data they have today.

Challenge of Visualization with BI

The other challenge is visualization. There is often the pressure to use technologies used by other parts of the business, where many organizations invest in advanced business intelligence (BI) technologies and efforts. Some BI tools that can do anything you ask and charge you to do it. But experience also tells us that companies often overbuy and aren’t prepared to handle what they get from the tools when they are not ready for them. At some point, good visualization will only get you so far if you are not ready to manage it. If the data coming out is not good, it doesn’t matter how cool the visualization is. Making decisions on bad data is never a good thing.

In a similar one-on-one discussion during a recent conference, a new CPO of a large manufacturing organization shared how organizational effectiveness and spend analysis are a priority to his organization. While a BI tool was selected by IT to give them visibility across the organization, the lack of category knowledge in his nascent procurement team has made it difficult for him to make much progress in his effort at mechanizing spend data and required an additional dashboard configuration.

Coupled with the lack of deep category knowledge among members of his team, today they aren’t getting the insights from the data for how they want to see it. On top of this, the challenge of getting a new IT person on staff to help with spend analysis has further exacerbated their need for partnering with a spend analytics provider that can provide both procurement expertise and data management skills.

Spend Analysis: An Iterative Process with Human Expertise

From SpendHQ’s perspective, solving the challenge of spend data and visualization is not always about putting all procurement under one technology roof or the latest in analytics dashboards, but in the experience in managing spend data from potentially many different sources. As the only solution in the market designed and built by sourcing professionals who use it every day, SpendHQ’s spend analysis requires a blend of data optimization expertise combined with visualization with its intended purpose from a practitioner’s lens.

Moreover, while procurement organizations internally are often good at the collection of data for spend analysis efforts, what many tend to lack is the category expertise. In this regard, our experience shows us that we are often brought to identify and capture cost savings opportunities, they quickly discover that their data is inaccurate or unusable from a sourcing perspective without significant cleanup work.

As part of any deployment to spend analysis, a key success factor is getting a true north understanding of your spend data, which is not going to be a one-and-done effort, but an iterative cycle of data optimization. This means in the first phase of spend analysis getting data accurate to the point of getting core initial reports around spend is a starting point. This also means an ability to get early insights out of the data to understand supplier relationships that cut across spend categories and identify low hanging opportunities in sourcing. During this time, it also means getting categories more accurate, and that often requires tweaks to categorization based on business unit feedback.

With second and third year maturity deployments of spend analysis, we see organizations often start getting into enriching the data with things like contract management, diversity spend and even more sophisticated data combinations over time. For those that have gotten past the basics, procurement organizations also continue to invest in talent and technologies that may cater to their needs. But the glue and sticking point is the foundation of the data as an essential element of getting the insights that they need with the wider data sets (both internal and external) that may be applied.

Spend Analysis Still Needs Humans

As the new currency in a digital world, understanding spend data is the foundation to acting and a precursor to any digital transformation effort. Yet procurement professionals often indicate that they still struggle with the foundational elements of getting basic spend analysis right, let alone introducing new digital technologies like AI into the picture.

There is no question that technology continues will evolve at a rapid pace, where enhancements in AI are rapidly augmenting human capabilities for collecting and recognizing pattern recognition in ever larger data sets. But even the academic and business experts in the field of emerging technologies would agree, we are not quite there yet for true “cognitive intelligence,” where existing technologies in machine learning, natural language processing and robotics still require human oversight.

Whether it be companies in the market for spend visibility for the first time or those looking to focus on spend analysis and visibility to engage digital transformational efforts, organizations will, for now, still need to get the basics of spend analysis right with human interaction and expertise combined with innovative technologies that will evolve and improve over time.

Constantine Limberakis is SpendHQ’s product marketing director.