How much effort do you need to cleanse, categorize and analyze your spend data?
How much effort do you need to cleanse, categorize and analyze your spend data? and what are your main issues?
I need your help to build an expertise benchmark on how hard it is for international companies handle with large spend volume data, lack of categorization, poor/dirty purchasing and suppliers data and overall... without a single version of the truth.
We offer an innovative automated solution to break down these issues, and we are always looking for new informations from procurement professionals to keep improving.
Thanks in advance for your cooperation, and for me it will be a pleasure if someone want to chat, maybe I can help you too!
Hi Tommaso, there are two activities you need to run: (1) Cleanse and normalise data (get rid of "dirty data") and (2) Implement data governance policy and processes (no more "dirty data" in). In terms of people, a top management sponsor, people assigned at each level with clear roles and responsibilities, and an ERP specialist. On (1), there are providers of data cleansing and normalisation, which use AI tools and their access to industry databases. You give them all sorts of data (e.g. invoices, POs, etc.), they "dump" those into their AI solutions, and you get your data classified. You then work on exemptions only (instead of having to conduct a "item by item" clean up).
Analysis of spend is a separate activity. Once you have your ERP data cleaned and people follow the new data governance rules, you can either use the ERP reporting functionalities, use BI tools to create reports (e.g. Power BI) or purchase a spend analysis software that will read, interpret and provide recommendations for action based on historical data. The first two don't provide recommendations, and you will need to analyse and find opportunities yourself, whereas the latter is an "intelligent" tool.
Hi Tommaso - I grappled with this challenge in my last role. The problem in that role was twofold :
- The procurement reporting took a feed from the finance system. So as you noted, what we worked out was that there was a lot of dirty data. Mis-coding was a big problem, and often not a great deal of excitement from the Finance team to change given they had already advised their masters in the financials.
- But the bigger problem was that the feed was always live and updating - even after a month end, systems could be opened and data re-categorised. So any cleansing that you did in your own system was lost by the overwrite. Not taking the full overwrite meant that you missed updates to old data
If you could find a solution to that, you would be doing very well.
Good Question Tommaso...Data QUality is the most important part to feed any BI tool and sometimes is not considered an important task....
Hi Tomasso, I may be late providing our perspective, but the amount of effort is directly related to the efficiency of your systems and data management processes. Most P2P systems still provide a silo'd perspective on the entire supplier management cycle including spend management so the data is rarely as accessible and accurate as you would expect. Unfortunately all systems are also dependent on people and processes to maintain data quality and this is an area usually compromised when deploying the operating model. We have managed over 40 global outsourcing projects within the real estate and facilities management category and access to quality, reliable spend and service data is always the biggest challenge. The spend data is usually the easiest to capture but understanding what services you received for the money is a real challenge. Certainly within the CRE/FM category most of the P2P systems completely fail to capture what is delivered for the money (other than a basic mapping to a chart of accounts spend category). Unfortunately the quality of the data directly impacts the quality of the bids and the level of risk a client can transfer so the pain of collection is usually worth it.
I go through this on a daily basis and it is incredibly frustrating. I have spent so much time researching options and re-imagining processes but without buy-in from Finance and an enterprise-wide commitment to following new guidelines, it is wasted time.