This post is the last part of a bigger article which is titled “5 things you should know - and 2 things you better not forget - when building a data analytic environment”. It is about data analytics in general, but with a focus on building bigger solutions like a CCM (Continuous Controls Monitoring Environment).
The full article contains of several parts. The first five describe attention points that you should be aware of:
- Know what you want to know (aka list analytic questions)
- Know your systems (aka identify data sources)
- Know your data (aka examine data structures)
- Know your Analytic Tools (aka understand technical possibilities and limits)
- Know your customers (aka think about who receives the results and what they will do with it)
Then we focus on two things that you probably already know, but we emphasize their importance for that special topic of data analytics:
- There is a price tag to it (aka budget)
- You need someone who can do it (aka resources)
The first five parts have already been covered (they are linked above, so you can go back anytime). This is the last part, covering “There is a price tag to it” and “You need someone who can do it”.
Bottom line of part five was, that results provided to those parties should be on different detail levels, and different output format. This may require special tools depending on what will be provided and how:
|Result consumer ||Graphics||Detail level||Tools|
|Decision Maker||Solely||Birds view perspective||Dashboard|
|Business Analyst|| Partly||Summarizes and Details||Analytic tool|
|Accounting Clerk|| No|| Detail level||Exception Management, Excel|
Picture 6 - Result consumer overview
Now that all five prerequisites are covered, we “only” have to implement the CCM project successfully. In this last part of the CCM series we talk about two elements that you probably already know, so here are…
... two things you better not forget
We will be discussing the aspects of
- There is a price tag to it (aka budget)
- You need someone who can do it (aka resources)
Of course there is no need to shy away from doing data analytics in a CCM environment. However it is more expensive (at least during the implementation) than doing only none-structured ad-hoc analytics.
The key elements that have a price tag are
- Internal costs
- Content (Make or buy)
- Know-How Transfer
- Internal and external human resources
Our CCM project “Payments to critical countries” should be performed by proper Client/Server data analytics software for the reasons discussed in part four of this article. This might cost more than only the desktop version of that software. If there is a user-based component (e.g. who can access the dashboard results) this has to be taken into account as well.
Client/server software usually does not make sense without a proper server environment. So the hardware is an element you have to consider as well. Whereas standard software has lower system requirements, a CCM solution will need more iron and horsepower to run properly.
If software and hardware are in place, installation and testing will require time and technical know-how (even more for this complex client/server environment, SAP® data access and so on). Make sure that you have the internal costs for installation, testing and maintenance on your agenda.
We also discussed the aspect of getting some ready-made content. Maybe the analytic “Payments to critical countries” can be purchased as readymade solution. This is a typical “make or buy” questions. Buying content will cost money, but developing that analytics plus documentation internally (even if someone with appropriate know-how can do it) will eat up time as well and therefore cause costs and efforts.
After setting up the solution and the content, there is the aspect of know-how transfer. How to use the CCM software, where to click? How to interpret the results? What are the steps necessary for change or add analytics to that solution? Are there SAP® specific elements that need to be trained? It is always good to have the focus on key users here, but having that know-how distributed over several shoulders will reduce the risk that comes with a potential fluctuation of employees.
All these elements need to be taken care of by people, so the last bullet point above is titled with “Internal and external human resources”. But this brings us to the second aspect that this article covers “You need someone who can do it (aka resources)”.
There may be a lot of people in your department, with an in-depth knowledge regarding a lot of relevant topics. But what this article showed as well is the immense need for a mix of
- Technical skills
- Process understanding
- Business / Accounting know-how
- ERP system know-how
- Analytical thinking
- Communication skills
You might have realized how important technical skills are when we discussed tables, fields, data structures and the concept of relational databases in chapter three of this article. Part of that was an explanation of different techniques how to find the data and to understand how the process logic is reflected in the database.
The business process understanding was emphasized when we worked on the analytic question in chapter “Know what you want to know”. Together with the requirement of knowing your business really well these are the prerequisites for making a good and detailed enough list of analytic questions.
Business / Accounting Know-How are related to the process understanding. Especially if there are analytics in context of Finances, Accounting or Controlling a basic knowledge about that is mandatory. If someone should analyze and understand the purchase-to-pay process, invoices, G/L accounts and Cost Centers, or incoming and outgoing payments, we have to deal with T-accounts, debit and credit posting rules rather sooner than later.
ERP system know how (in our case, knowledge about SAP®) was necessary several times already. In part one we had do understand how the process is implemented in the SAP® system; “Knowing your systems” we had to identify the relevant SAP® version, system, and talked about users and authorizations. When it came to finding out about the table and field names, we had to use SAP® transactions to identify the underlying data structures.
Analytical thinking is quite self-evident. The ability to structure an analytic question as well as the roadmap to answer it; logical thinking and being able to translate and transform a business aspect into a technical solution – all this is part of the analytical thinking.
Last but not least, communication skills (as usual) do help a lot. In data analytics it might be even more required than in other areas, because sometimes we need to talk about heavy stuff like risk, Compliance aspects, human errors, process weaknesses or even money that is identified as “lost”. People feel responsible for this and maybe as well “made responsible” for this when raising such questions. Also, during the implementation, there will be a learning process, and round-table discussions where managers, IT specialists, business analysts and accounting clerks will have to discuss the same topic from different angles. This needs to be balanced by a solid set of communication skills.
All of this sounds reasonable, but the thing is, you need some heads where all this know-how is combined within the same person. This will be a very important factor for success. That skillset in combination is hard to find, as often people do know technical aspects very well OR business aspects OR have a good know-how regarding SAP®. If this mix does not exist to that extent – bring in external resources who will do the know-how transfer. I do not want to sound selfish here, as obviously we are in that business. However it is a critical success factor, and – especially in the starting phase – things will go a lot better and faster and with less frustration if this mix of skills exist. So after this walkthrough of getting a CCM project started, and what needs to be considered, the importance of keeping the resources in mind is obvious. Yes, there are a lot of things to be considered (five important aspects have been explained in detail in this article); and yes, it will cost money, time and brings the challenge of having real all-rounders on board who make this project a success. However it is a journey worth to travel; having a profound data analytic approach is not nice-to-have, nowadays it is mandatory. There is a nice McKinsey article about that on a more strategic level, which nevertheless shows the urgency to push and establish data analytics– it is linked here, as you may want to check out in addition to this hands-on series.
I hope you enjoyed reading it as much as I did when writing it. There are a lot more things to be said about data analytics, so keep on checking out our blog here. For any comments, questions or request, feel free to write us at email@example.com.
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