SSO's & Small Entities (Chapter 4): Case Study Data Collection

This article is part of an on-going series by Pedro Moreira, based on his experience at Siemens’ Shared Services operation, where one of the projects he ran was a migration within the company’s finance group. Moreira focused his Master’s thesis on the impact of Financial Shared Services, with a special focus on how Shared Services supported the migration of a small Siemens entity into the Global SSO.

His research shows that as SSO transitions generally try to keep complexity to a low level, they tend to leverage a standard or generic approach to all business units. When dealing with smaller entities, however, this creates a danger, as their rules, reality and dynamics are unique. Small entities, with Finance functions staffed by 10 or fewer people, generally have broader responsibilities within one role, so services that would not be core to the SSO need to be considered as part of the migration. This creates added cost and complexity.

Moreira recommends that companies rolling smaller entities into their SSO should do so via a special "small entity migration wave".

"The findings and recommendations of my thesis are quite important in terms of analyzing common organizational structures within an SSO, understanding how Shared Services serves small entities, and, also, how it can ultimately lead to less than optimal savings and operational efficiencies", explains Pedro. The recommendations he makes point to organizational changes and measures required to reverse the negative impact, as well as tips on where and when this can occur.

"Since starting my thesis, I have used SSON’s online resources as a source of information and ideas on the latest SSO developments and technology," Pedro explains. "Now, I'd like to contribute back to this community by sharing the knowledge I have acquired."

Introduction

In my last article, we discussed methodological framework and assumptions and how they link to the case study. In this article, we’ll go through the data collection and see how this also links to the selected methodology in our analysis. Field work data was collected from November 2013 through to March 2014, the timespan that on-site work was done. Data analysis took place from April 2014 to June 2014.

Secondary Data

This type of data is useful for reference, comparison and contrast. Scientific databases, books, articles and published information for instances, were used in order to analyse key related macroeconomic factors (e.g., literature revision and methodological framework from previous chapters), but also the case study entity financial information.

Analysing the entity’s public financial statements from the previous five years (09-13) we can see the trend but more importantly we begin to understand the entity’s dimension, group wise, in terms of revenue, expenses and profit. Dimension is an important factor, to which we’ll dedicate some time in later chapters, as it’s key for the obtained results and as well as the recommendations.

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In the table below, we see that the trend of personnel expenses follows the trend of financial performance. From direct observation (primary data) we conclude that this is most likely related to variation in the number of production workers, considering a delay between revenue drop and production FTE reduction. Specific data regarding the cost of the finance department would have been interesting to analyse in this context, but was not available.

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Primary Data

Interviews

Several interviews were carried out with relevant entity personnel, including management, with different objectives throughout the study:

• Obtain the entity’s agreement and participation on the study
• Evaluate the temporal pertinence of the study
• Discuss the variables in study
• Agree on planned field work
• Discuss and agree on questionnaire metrics/questions
• Population to inquire
• Potential technical issues
• Field work results analysis and discussion.

Later in the work, I had the opportunity to interview Kai Zabel, author of the article "Shared Services for Smaller Entities". Kai’s expertise provided great insights and perspectives on the results analysis and conclusions of the work and his article is highly recommended and valuable for those dealing with small entities in a shared services environment and/or interested in understanding these particular dynamics. We’ll discuss this interview and the analysis of Kai’s article in the context of this study, in future chapters.

Direct Observation

Throughout the field work, a total of three visits were made to the case study entity, each spanning 2-3 days. During these visits we observed a general mood of uncertainty and dissatisfaction related with personnel reduction (not directly linked with the finance migration). In the finance department, the same general mood was observed. Specifically, the feeling regarding the new work processes generated dissatisfaction, demotivation and apprehension. In terms of numbers, the original seven FTEs at the time of migration had dropped to six, with one more foreseen for later in 2014.

Questionnaire

The questionnaire was created in consideration of the data that was collected regarding the finance transition, the literature revision and the established methodological framework. The objective was to understand the perception in the entity of the impact resulting from the finance migration to the shared center.

The questionnaire was composed of 60 statements and 3 questions, all grouped into categories (these were not visible to respondents) by relevance, as we can see in the picture below. Each statement represents a metric with a metric category. Google Docs was the tool used to deploy the questionnaire. 

The questionnaire starts with three YES/NO questions, whose purpose is to determine the validity and perspective of all the remaining answers in the impact study. For the remaining statements, the Likert scale was used, meaning that for each of the metrics/dimensions we can get individual perceptions and determine the impact of the finance migration. The statements are a product of what the literature revision showed us – namely that the impact of a finance migration is positive, so this reality is assumed and it was up to the respondents to validate this or not.

The categories of "Accounts Payable", "Accounts Receivable", "Accounting/Reporting" and "Operational Efficiency" were set to measure the impact specifically in the finance department. In "Process Quality" we sought to determine the quality of the new process, keeping in perspective the old one, and understand if a quality improvement was perceived. In the sections "Process Use" and "Process User" we’ve measured the impact in the use of the new process and in its users. In the "Financial" category, the statements were aimed at measuring the impact on the entity’s financial performance. The "General" category was created to allow the measurement of perceptions, even for people indirectly affected with the process change. The last categories of statements "Communication" and "Alignment" were created with the objective of measuring the quality of communication and alignment of objectives between the entity and the SSO.

Regarding the inquired population, we had a total of 75 people, spread through the different departments (see table below). Taking into consideration the nature of this study, we expected that the personnel from the finance department were the most affected by the finance migration, though this was not an exclusive influence, e.g., Purchasing and Sales suffered some smaller impact. In any case, it was accepted that a large part of the population could only be used as control.

Time Horizon of the Study

The impact study of the different metrics/variables requires the consideration of a temporal timeframe that allows the analysis of the "pre finance migration" situation, observation of transformation, and lastly, the result of that transformation or the "after finance migration" phase. With regards to our case study, this timeframe spanned from January 2011 until March 2014.

Note: In the next chapter we will analyse the questionnaire results and comparison of those with the hypothesis – a step by step overview covering the sample analysis and all metric categories.