Shared Services and Small Entities (Chapter 3): Milestones for Shared Service Implementation

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." ________________________ As referred in a previous article, companies have been working hard to increase productivity, reducing costs and improving management, since the eighties. In this context, we’ve witnessed the emergence of Financial Shared Services. However, to make this transformation, a hierarchy of operations and process improvements must be considered. According to Schulman, Harmer, Dunleavy and Lusk, authors of the book "Shared Services: Adding Value to the Business Units", this hierarchy is composed of three main milestones – each containing three intermediate milestones. These milestones need to be sequentially fulfilled before moving on to the next one. They include: 1. Responsibilities a) Governance – Strategy development and objectives; b) Responsibility – Clear definition of who is responsible for what; c) Measures – Measures that generate accountability; 2. Efficiency a) Processes – Process reengineering and/or process improvement; b) Systems – Rationalize and improve hardware and software, incorporating the latest advances in IT; c) Economies of scale – E.g., through personnel redundancies or using lower pay labor markets; 3. Effectiveness a) Competences – training, including adapted training to the new organizational reality; b) Service – Optimization of value-added activity and increased customer service mentality; c) Organization – Organizational adaptation and restructure. When we analyse the three milestones, we can see that in order to obtain gains in efficiency, companies employ process reengineering/optimization, while also updating and improving their hardware and software. These improvements are crucial for the successful implementation of a shared services and the respective activity migration from client entities. Our case study focuses on the efficiency impact from process reengineering/improvement as a consequence of a finance nearshoring. Process Impact Analysis Framework The Balanced Scorecard presented in 1992 by Robert Kaplan and David Norton allows companies to review the impact that activities have on critical dimensions of corporate performance. The Balanced Scorecard has evolved since then, allowing new value added indicators to be incorporated and can be used to carry out health checks during the life cycle of a project. [click to enlarge] Conceptually, it’s possible to measure performance in four different dimensions: 1. Financial Measures, i.e., growth strategy, profitability and risk from a shareholder perspective; 2. Sales and Marketing, i.e., value creating strategy and differentiation from the customer perspective; 3. Operations, i.e., strategic priorities of the several business processes that create customer and shareholder satisfaction; 4. Innovation, i.e., creation of priorities that stimulate and encourage organizational change, innovation and growth. Sedera, Rosemann and Gable, in their "Measuring Process Modelling Success" study, created a model to evaluate the impact of process change that adopts the four dimensions of the Balanced Scorecard and links them to the process impact of their model (see picture below). [click to enlarge] The methodological framework, therefore, consists of six dimensions (Modeller Satisfaction, Process Model Quality, Model Use, User Satisfaction Process Impact and Organizational Impacts) along a timeline. The arrows depict the intermediate nature of each dimension and how they influence one another. Modeller Satisfactionis unique in this model. It refers to the measure in which the process engineers believe in the achievement of the proposed objectives and the efficiency of the entire process. It was included to understand the effective attitude of the process engineer and the perspective of the developer. The Process Model Quality dimension is defined as the extension in which all model properties are fulfilled to satisfy process users’ needs in an efficient and effective manner. Model Use is the full extent of process application. The non-use of the created processes represents lack of success and waste of resources. Given that success is contrary to failure, it’s often assumed that the use and application of a model represents its success, however, it can be that this is not always true. Firstly, model use is difficult to measure. The use has to be voluntary and not forced in order to have analytical value. Secondly, real use may be different than reported use due to distortion in the collected data or other organizational problems. Lastly, different levels of use and different types of users make the data analysis even more complex. User Satisfactionmeasures the extent to which users believe that the process satisfies their needs of information and the initial objectives. The dimension of Process Impact measures the effects of the process change in performance, i.e. in the processes and functions that underwent change. Process Impact is a subsection of Organizational Impacts, supposing that the process improvement will reflect itself on the organizational performance, e.g., faster processes will influence greater profits but only indirectly, due to their intermediary nature. Temporal Pertinence The point in time where an investigation is conducted is critical and can have a great impact on the obtained results. Which phase is most appropriate depends on the perspective. There are two perspectives, the one from the process engineer and the one from the users (perception of applicability or use). The first one is measured during the creation/engineering phase, the second one after implementation and the processes/model has started but not entirely completed; in other words, at the point in time where new/modified processes are being applied with the support of several system life cycle stages. According to Sedera, Rosemann and Gable there are four distinct phases (A, B, C, D) to consider in process engineering/reengineering: [click to enlarge] Period "A" is ideal to collect information from the perspective of the process engineer, as the experience is still recent and he or she will be able to provide a more accurate perception. However, at this point there is no process application let alone possibility to evaluate from the user’s perspective. Period "B" is still not adequate to collect information from the users, as they still don’t have enough experience or time working with the new model to be able to identify and recognize the true impacts (positive or negative). Period "C" is ideal to collect data from the users, the project phase will already be completed and the users will have enough experience for an evaluation. As time goes by (Period D), external factors beyond just real impacts of the new model will emerge and influence perceptions, and users have the tendency to forget the real impacts and implications of the model, inflating or deflating the results of an evaluation. Combining this theory with what we know about the operations and finance process migrations of the Siemens Global Shared Services (GSS) was the next step. On the strategic level of activity transfer and process implementation, the GSS uses the LIFT-DROP-CHANGE method. In the LIFT-DROP phase, a set of specific, pre-determined activities (processes) are transferred from the client entity/business unit to the GSS. The second phase, known as CHANGE or POST BUNDLING, has as its objective the active optimization of the processes, make them faster, more efficient and light. The heart of this phase is the program Process Improvement for Accounting (PIA). Specifically, in our case study (see picture below), the project planning, workshadowing and knowledge transfer happened up to January 2012, the point where the migration of processes was completed and the application of the new model began (Go Live). Until this point we were in the phase of process engineering, altering/creating the processes; the "Go Live" represented the concretization of the LIFT-DROP phase. From this point onward it’s considered a CHANGE phase, where theoretically we should expect the impact of the PIA program on the finance activities to start happening. [click to enlarge] After the period of "Roll out and Communication" we enter the subsequent period that comprises the comprehensive application of the model by the entity users. It is during this timeframe that our evaluation at the entity level was conducted. Understanding at what point in the project the investigation would be conducted required analysing the project cycle and interviewing key entity personnel to understand the current standpoint. If more time had been allowed to pass, the risk of a bias evaluation due to the reasons outlined above (external factors, PIA application, time) would increase, preventing an investigation that could determine the impact of the model change – i.e. determining the impact of the finance migration by analysing the model in use before the migration and the one after the migration, from a user (entity) perspective. In the next chapter, we’ll discuss the collected data, both primary and secondary. These will include a financial overview of the entity, interviews, direct observation and questionnaires. We will then see how these derive from our methodology. [eventpdf] Editor's note: If you like this content – please share it with your social media groups across Twitter and LinkedIn. Just use the buttons on the left of the page. Please also add any comments below, to contribute to this discussion. Note: Other articles in the series: Introduction: How to Maximize Savings And Operational Efficiencies When Working With Small Entities Shared Services and Small Entities (Chapter 1): Globalization and the Shared Services Evolution Shared Services and Small Entities (Chapter 2): Organization, Objectives and Relevance Shared Services and Small Entities (Chapter 3): Milestones for Shared Service Implementation SSOs and Small Entities (Chapter 4): Case Study Data Collection This series will be continued next month...

Shared Services and Small Entities (Chapter 3): Milestones for Shared Service Implementation

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