CCM (Part 6) - 5 things you should know - and 2 things you bet­ter not for­get - when build­ing a CCM da­ta an­a­ly­tic en­viron­ment

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:

  1. Know what you want to know (aka list analytic questions)
  2. Know your systems (aka identify data sources)
  3. Know your data (aka examine data structures)
  4. Know your Analytic Tools (aka understand technical possibilities and limits)
  5. 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:

  1. There is a price tag to it (aka budget)
  2. 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”.

Five things you should know ...

The first five parts covered things that I see as “essential” for building a CCM environment. We had a look at the following steps:

Picture 1 – The five aspects you should know

The first step, labelled “Know what you want to know”, was about a getting proper business understanding and stating as-detailed-as-possible questions that can actually be answered. Only by knowing your business well you can make a good list of analytic questions. The area we were interested in was “Compliance”, the topic “Payments to critical countries” and the detail questions that were raised we stated as follows:

  • “Identify payment transactions that have been done in context of partners like vendors, or customers, or even where an expense account is directly debited.
  • Create a list of these transactions and identify the payee’s bank country for those payments.
  • Match these detail transactions versus a list of countries that are seen as critical because they are on the embargo list, known as tax haven or having a Corruption Perception Index > x.”

In step two we talked about the importance to “Know your systems”. We found out that our payment data is on an SAP® system “SY2”, running SAP® ERP ECC 6.0, and containing the financial transactions for all companies worldwide.

Picture 2 – Identifying the correct system

Based on that we identified the data owner, and then followed the process of requesting a user with appropriate read-only rights to access the data.

What data actually is necessary we discovered in chapter “Know your data”. We went from identifying the tables to finally identifying fields and understanding the logic and relations between the tables. Part of that was an explanation of different techniques how to find the data, and the top down approach. We ended up with a list of tables and fields, which for our example could look like this:



Element / Process step
Vendor master dataLFA1LIFNRVendor number
Vendor master dataLFA1LAND1Vendor country of residence
Vendor bank accountsLFBKLIFNR Vendor number
Vendor bank accountsLFBKBANKSVendor bank country
Customer master dataKNA1KUNNRCustomer number
Customer master dataKNA1LAND1Customer country of residence
Customer bank accounts KNBKBANKSCustomer bank country
Customer bank accounts KNBK KUNNR Customer number
Payment run transactionsREGUHLIFNR Vendor number
Payment run transactionsREGUH KUNNRCustomer number
Payment run transactionsREGUHLAND1Vendor country of residence
Payment run transactionsREGUHZLAND Payees country of residence
Payment run transactionsREGUHZBNKSPayees bank country

Picture 3 - Examine data structure: Table and Field list



We know the question, we know where the data for the answer is stored, and we are also aware what data is necessary. The attention points regarding the tools for data extraction and the analytic tool have been defined as well. The most important aspects are listed in the following checklist:




Data Extraction Tool
Data Analytic Tool
Mass data capabilityMass data capability
Read-only accessRead Only
Delta-DownloadsClient/Server capability
Correct target formatsTransparency
Data PrivacyContent
Output formats

Picture 4 - Checklist for data extraction and analytic tool


At the end of part four of this series, we briefly discussed the meaning of having different output formats. As you may get different requirements from different types of “result consumers”, a certain flexibility is important. You have a manager who only needs KPI information; on the other hand you have an accountant who should look up the details.

Which types of result consumers (audience) you might encounter, and what this means for our example scenario of “Payments to critical countries” we discussed in part five. We identified the following parties:

  1. Manager / Decision Maker
  2. Business Analyst
  3. Accounting clerk

They will do different things based on or with the results that are generated by the data analytic routines of our CCM solution. The following picture differs between an “FYI only” part and concrete “Follow-up actions”.

Picture 5 – How to proceed with the results

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
Detail level
Decision MakerSolelyBirds view perspectiveDashboard
Business Analyst PartlySummarizes and DetailsAnalytic tool
Accounting Clerk No Detail levelException 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

  1. There is a price tag to it (aka budget)
  2. 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

  • Software
  • Hardware
  • 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  info@dab-gmbh.de.

To contact the author you can also use LinkedIn or XING (you may have to login first before you can access these links).

LinkedIn: http://de.linkedin.com/pub/stefan-wenig/54/1b8/b30

XING: https://www.xing.com/profile/Stefan_Wenig2?sc_o=mxb_p

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