The Oft-Neglected Essential In Digital Transformation: Steering Model Redesign

Reinhold Exner

Part 1 in the Steering Model series

Every executive team beginning to map out a transformational strategy – redesigning business models, offering new services, making acquisitions, going digital – needs to translate that strategy into concrete activities. And once executed as operational processes, that strategy can be determined to be effective only if the impact can be measured. For the CFO, this means instituting a steering model that maps directly to the transformation being undertaken.

Defining measurable targets

A “steering model,” in short, is a framework for operationalizing corporate strategies and objectives into measurable targets. These targets are typically measured by so-called key performance indicators (KPIs). A steering model, by nature, is a top management concern, hence it’s owned by the board, CEO, and most commonly by the CFO.

All companies have in place a steering model based on financial KPIs, including P&L, balance sheet, cash, or cost-related KPIs. However, due to past developments (like introduction of balance scorecard and learning based on economic crises), many companies have broadened their steering model beyond pure financial KPIs. One of the main reasons for doing this is to improve insights into driving factors (leading indicators) for the targeted strategic KPIs.

An opportunity to better support the business

On our consulting team at SAP, we work with companies that recognize that their steering model redesign should be not only business-driven, but also a more technology-driven opportunity to support the business in a better way. This often leads to similar requirements to validate future readiness of the current steering model.

We often hear, for example, that the steering model is “historically grown,” or that the steering model “was developed 10 years ago” and never challenged systematically to improve. Others state that they don’t get the data out of their systems, which are far too aggregated, and that the processes in place to extract the data are cumbersome. And some complain that there is no proper master data in place: “We are thinking and acting in silos.” In many of these cases, company management feels a “need for change.” But how do these questions lead to a new steering model – and how does this impact the ability to ramp up a digital transformation journey?

How the steering model drives future performance capabilities

McKinsey defines a transformation as “an intense, organization-wide program to enhance performance (an earnings improvement of 25% or more, for example) and to boost organizational health.” So a corporate transformation is a huge step from the current situation to the future state, with typically a very high level of inspiration and ambition. A transformation aims for a holistic reconfiguration of a company, such as to boost top-line growth, cost efficiency, operational excellence, and customer satisfaction.

Take, for example, a company that chooses to shift from decentralized responsibility to a model emphasizing more centralized, controlled, and managed decision-making. This change implies new centralized reporting requirements, which need to be reflected by the transformation. This is by no means a purely technical task of providing already existing reports to new users. Instead, the company needs to enable the centralized teams with the same level of insight enjoyed by those who are closer to the action. It’s a business change-management task that should be driven by company leadership – with a technical implementation, of course.

Or a company might face difficulties regarding KPI comparability due to partly unharmonized KPIs, organizational models, master data, and processes. It’s obvious that aiming for comparability, improved transparency, and reliability will lead to new process design, new setup of responsibility areas, and hence a steering model redesign. Strong top management commitment will be required to foster a significantly improved cross-departmental alignment of designing the new landscape, complemented by strong program governance.

Addressing steering model redesign from the outset

A ramp-up phase is typically the early phase of preparing for the upcoming transformation. This phase encompasses, among others, giving direction by clarifying a mandate for the transformation program. This involves sponsorship as well as stakeholder alignment and setup of a sustainable foundation like internal and external recruiting, knowledge transfer, and initial organizational change-management measures. Change management should include clear and systematic change communications and other essential onboarding activities.

During the ramp-up phase, top management needs to be very clear about the transformation objectives, including a mandate for a revision of the steering model. If this journey takes some years, it needs to be clear that by reaching the end of the transformation journey, the existing steering model must not be outdated. For this reason, it’s essential that if there are any indicators towards a new steering model, these signals are taken seriously and are sufficiently reflected in very early stages of a digital transformation journey: in the ramp-up phase.

There are many aspects to consider as you embark on this undertaking. My next blogs in this series will explore further.

Oxford Economics recently surveyed 1,500 finance executives to understand the attitudes of finance professionals toward the function’s changing requirements and challenges. Read the full study, “How Finance Leadership Pays Off: Six Ways CFOs Stay Ahead of the Pack.”

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Reinhold Exner

About Reinhold Exner

Reinhold Exner is a principal business transformation consultant with SAP. He has 14 years of management experience in various controlling functions and has worked with SAP for 8 years. He supports international operating companies in optimizing their finance organization and processes leveraging SAP solutions. Reinhold holds a degree in Industrial Engineering (Dipl. Wirtschaftsingenieur) from Technical University of Karlsruhe, Germany.