Many CFOs sense that there are pockets of inefficiency in their organisations. They then contract one or more consulting firms to help rationalise spend and streamline operations. The theories brought to the table by the consulting firms are fantastic and stem from either deep experience or benchmarking.
They perform a series of interviews, analyse the financial data to highlight specific cost inefficiencies compared to the benchmarking, and deliver a report with prioritised areas to cut costs. There is usually little surprise over rationalisation as the primary candidate turns out to be salaries and labour costs. Let us look at the issues at play here.
The structured process used to analyse metrics such as speed and resources associated with tasks or processes and compare them across companies, industries, and countries to identify and quantify improvement areas. Although benchmarking is a practical way to understand how efficient a process could become or what the business could gain by changing specific practices like outsourcing or functional specialisation by creating business silos, this approach has several pitfalls for the client. It does not consider the indirect costs associated with the situation in the first place. A better alternative is to understand the overall maturity of processes, data, and management systems within the functions and tasks to pinpoint whether any productivity gain would result from improving the process, the technology, or the management style, before reducing something as apparent as headcount.
When consultants request and analyse financial data, some hurdles inhibit the process. The consultant usually has a specific framework for economic analysis. Often, this data is not available or low quality, resulting in the consultant either using assumptions or benchmark data to make the framework feasible. The outcome of this process is a highly generalised view with unverified assumptions.
The consequences of making the wrong decisions
The problem with cost reduction without precision is that organisations cut into growth capacity. The typical example from the professional services industry is to remove employees when there is not enough work to keep them busy and profitable. In conjunction, the firms put substantial effort into the sales process, only to be oversold and then rushing to recruit new employees or contract those they had just laid off at a premium.
Unfortunately, this example spans many industries where management teams do not have a coordinated planning and reporting approach. So, where to from here?
It starts with a plan
Organisations usually have complex structures and processes to navigate to get the correct data to make the best decisions. Before we get the data, though, we need to understand the organisation’s direction. This is usually captured in the organisational strategy, based on the business model, supported by an operating model with processes. By understanding the organisation’s direction, supported by operational processes, we can then start considering which data is required from the internal and the external environment.
Then, we need the right data
The rate of data growth is a topic for a different paper. Sufficed to say, there is a lot of it floating around inside and out of the organisation. The challenge is to find the right data to support the analysis part of the decision process. Typically, an organisation will have an enterprise resource planning system, like SAP, Oracle ERP, or Microsoft Dynamics, who developed these systems to process the transactions and events depicted in the operating model.
A crucial component is required to link the overall strategy, the long-run plan, to the ERP data. The link is the long-run and short-run plans and forecasts. The long-run plan breaks down all the strategy’s ideas by the different operating model elements and cascades it to the various departments and processes. The analysis process compares the data reflecting the operations to that of the planning process. When looking at the actual vs planned and forecasted variances, it helps to understand the performance relative to the original plan. The real value is unlocked by looking at the drivers of results to identify how these drivers could be addressed to deliver the same quality for less effort and at the same or lower risk level. The method is called driver-based planning and considers external factors such as market indicators, supplier risk, and turnaround times, allowing the organisation to identify additional capacity in the process that could be repurposed or removed entirely.
Driver-based planning is compelling due to its ability to demonstrate the impact of various internal and external factors on the planning and forecasting process. When an organisation performs integrated planning, driver-based planning also acts as the glue between the business’s parts, enabling an end-to-end view. The drivers are initially identified in a driver-based approach, starting with earnings before interest and taxes (EBIT) and breaking it down into the significant revenue and cost components. It might seem simplistic for the first level of a driver tree, but complexity is soon introduced when including product mix, product profitability, labour composition, and external factors into the driver tree. The first iteration of the driver tree could be rudimentary, but as data is introduced and incorporated to test the model or models’ different components, these models become more sophisticated and accurate.
When to introduce technology
Most of the modelling could start in a tool like Microsoft Excel, but it soon becomes clear that Excel is not the best solution for massive data volumes and sharing models for input and analysis. Excel also has an unacknowledged risk of audibility. When a well-meaning, intelligent modeller makes a mistake in small business rule or formula, it could have dire consequences when making the wrong decisions. Established Performance Management technologies have come a long way to aid the planning, budgeting, and often, consolidation processes of a business. The technologies have improved immensely in speed, managing large data volumes, and enhancing integration from various systems in recent years.
What does this mean for cutting costs without removing capability?
Cutting cost without cutting capability means that the organisation could now build forecasting scenarios with data at a very granular level and understand its profitability and cost implications based on the drivers identified and how various processes interact in integrated planning. As a result, the organisation avoids unintended consequences of cutting areas important to other processes. The example is reducing inventory to just-in-time levels without understanding the risk of those stockouts, a challenge highlighted during the COVID-19 pandemic. Plant closures and international freight stoppages led to in-country manufacturers and distributors experiencing outages and stockouts and, ultimately, lost revenue. The problem could have been avoided by planning for that additional emergency materials.