• 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!

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  • Answers (5)

  • Ricardo Yoshida

    12/11/2020 01:37AM

    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.

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    Tommaso Avanzo Thanks Ricardo! I completely agree with you on both the process and the fundamental point of having clear data and a valid application for spending analysis

    12/11/2020 10:56AM

  • Darren Stafford

    28/09/2020 07:59AM

    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.

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    Tommaso Avanzo Thanks Darren for sharing your experience, we have a solution and we are already serving international companies with big results but we must keep improving and help companies in recognising their issues are solvable thanks to new technologies and modern applications. Procurement is becoming more strategic day by day, and complex decisions need to be taken with good visibility!

    30/09/2020 05:32PM

  • Stefano Sollazzo

    28/09/2020 07:34AM

    Good Question Tommaso...Data QUality is the most important part to feed any BI tool and sometimes is not considered an important task....

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    Tommaso Avanzo You are right Stefano, good data means correct decisions... :)

    30/09/2020 05:14PM

  • Colin Hall

    20/10/2020 10:09AM

    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.

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    Tommaso Avanzo Thanks a lot Colin, I appreciate your contribution!

    20/10/2020 01:24PM

  • Karen James

    15/10/2020 12:39PM

    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.

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    Tommaso Avanzo I can imagine Karen, enterprise commitment is the basis for the success of every project, and especially for digitalisation ones. Who is in chair must know that, thanks to modern technologies you can automate your processes and improve datas and its classification as well. And you can spend your time on most added value tasks, reducing wasted time (and moneys) and working on motivation ;)

    15/10/2020 01:41PM

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