It's Only the Beginning for Spend Visibility and Analytics Growth

Kevin:

Excellent points. It is indeed a common refrain, "Doesn't our ERP system provide all the insight we need for spend analysis." (In fact, Jason did a great expose on a certain "Black Paper" on this subject not too long ago.)

The best way to cut through this issue is with a real-world story of one organization's spend analysis journey. (I apologize in advance for the length. It's a short story, but long for a blog comment.)

For the purposes of this story, the company, whose name will be protected to avoid divulging their competitive edge, will be referred to as Global Tech Co.

Once upon a time back in the last century, Global Tech Co.'s IT leadership assured the supply management group that the spend analysis challenges would be resolved when the company standardized on a common ERP system. After the fact, the supply team quickly realized that ERP systems are built for high-level financial analysis and lacked the detailed, line-item attribute data needed for meaningful spend analysis. For example, ERP standardization reaffirmed what the supply team already knew – Global Tech Co. spent a lot on hardware. But the ERP data didn’t help commodity managers determine how much was being spent on high-end SPARC stations versus laptops. Nor could it shed insight into whether these items were being bought for development engineers or office administrators.

Global Tech’s next strategy was to assign standard part numbers to the items it purchased. This led to a proliferation of part numbers as well as differences within the part numbers. To continue our example in the area of hardware, part numbers were difficult to assign due to different models and configurations.

Global Tech’s next move was to dump spend data into a data warehouse with a snazzy reporting tool on top. This allowed the supply team to slice and dice spend data and create reports to impress their boss and friends. However, this approach still didn’t solve the core symptom: Global Tech lacked spend data detail that could support accurate classification and meaningful analysis. (Garbage in, garbage out, anyone?)

As a result, the supply team spent their time pulling spend data from the warehouse into spreadsheet pivot tables so they could sort it by attributes. But with key detail – like processor speed or memory – buried in the description, this information was hard to dig up. This lengthy and labor-intensive process forced Global Tech to continue to conduct spend analyses on a project basis. Worse yet, time and resource constraints limited analyses to Global Tech’s big-ticket spend categories.

Finally, Global Tech Co. adopted a solution that automated spend data extraction, classification, and analysis. Through the use of a business-rules engine the tool rapidly accessed and evaluated the line-item spend attributes and classify these to a common schema.

This automated attribute-based classification gave Global Tech the detail required for meaningful analysis, enabling the supply management team to improve spend leverage and develop informed sourcing and supplier management strategies. For example, the company has been able to change its hardware buying policies and practices, assigning approved hardware types and configurations for each role in the organization. (No more SPARC stations for the receptionist!) It also uncovered more spending power, such as hardware purchases that had been misclassified under office products.

Such insight and detail enabled Global Tech Co. to achieve additional 5% - 15% cost savings – depending on the spend category – through improved spend leverage, supplier rationalization, and new buying rules.

This automated spend intelligence approach enabled Global Tech Co. to be more systematic about spending analysis. The company auto-refreshes 100% of its spend data pool on a monthly basis, arming its supply team with the intelligence required to make and execute informed sourcing and supplier strategies across a much broader portion of Global Tech’s spend.

The moral of this story (in case you missed it) is that even if most of your spend data is captured within your ERP system (for it won't all be there), unlocking the secrets of that data requires you to access and make sense of more detailed attributes of your spend. This requires having the proper, knowledge-based tools to extract, cleanse, classify, and enrich spend data at a detailed level – all on a repeatable basis.

Tim should write for Harvard business Review (perhaps the secret ambition while being a journalist at Purchasing magazine?)... "As Sam Spend gazed out his window looking at the street below, he watched the people moving as slowly as the line-item transactions going to his spend warehouse. The analogy was not lost on thim. Would the exec's care even realize the gold hidden in the mountains of data, or would the data be lost like the thousands of pedestrians in street? He had to make them see, but how?..."
The problem with analytics ROI is getting the "I". It's the 'catch 22' of spend analytics.....
CFO: how much will I save this project
CPO: a lot. look at all the vendors claiming the savings. Aberdeen says it's 4984% returns.
CFO: how much will WE save?
CPO: we don't actually know until we do it, that's why we need to do it
CFO: but if we don't know, why should I invest at all?
CPO: Look, you'll have to trust me on this
CFO: like I trusted IT with the ERP and data warehouse projects?
CPO: this is different.
CFO: tell you what. use the ERP system. If you feel you have to use another vendor, get the CIOs approval. If you can't, run a pilot. re-engineer the processes. then come back to me with a funds request next year. buh-bye.
CPO: yeah, but, we're at risk from a regulatory standpoint. We can't even see where we spend our money?!
CFO: we're in compliance, and I'll send you the audit reports.
CPO: yeah, but this is different....
CFO: of course it is Sam. Oh, what do you know, our 30 minutes is up. Have a great holiday Sam, goodbye.
And a great thanksgiving to you all, my foolish bloggers.