Monitoring and benchmarking is essential for strategic SCM. The measurement of business performance is deeply grounded in the backward-looking accounting disciplines of recording profit.
The supply chain is a complex system with many interfaces and dynamic interactions. It is a significant challenge to define the measures at each point in the chain that are appropriate and consistent with the overall desired results.
Performance management in the supply chain is about setting goals within and between functions that will lead to the desired results with balance and without conflict. Ideally, these goals are then embedded in the fabric of the management measurement and reporting of the functions of the firm and its customers, suppliers and service providers.
Each function is responsible for delivering its part of the chain to the performance objectives; and when things do not work as planned, the requirement is for failures to be identified and recovery actions mounted. Learning organizations will take the lessons of actual performance and the experience of failure and recovery to adjust the goals across the chain, acting as ‘stewards’ of the supply chain. This stewardship role is a key responsibility for supply chain managers, since they often do not have functional responsibility for all the chain, albeit they are judged and rewarded on its overall performance.
There are two requirements of performance measurement in the supply chain:
- understanding and embedding the value and importance of measurement in a strategic framework for supply chain management;
- creating a predictive framework of supply chain risk.
The essence of business is to generate profits and cash from satisfying customers through its investment in assets and capabilities.
Performance measurement, reporting and management, therefore, need to come closer to the reality of serving customers and the operational demands of day-to-day decision making. In the context of both business direction and the detail of the supply chain, the task of measuring performance unpacks into many layers of detail; it is a subject in its own right.
What to measure against?
As already indicated, there are a number of different approaches that can be adopted to determine appropriate goals. These range in sophistication from very simplistic internal year-on-year comparisons to quite detailed externally related engineered standards. Most well-developed systems are internally budget-oriented, but are also linked to external performance measures.
Historical Data
Systems that merely compare overall activity costs on a period-by-period basis may not be providing any useful information that can be used to monitor operational performance. As an example, a measure may indicate that the cost of distribution for a company has reduced as a percentage of total revenue for this year compared to last year. Without any background to this measure it is impossible to be sure whether or not this is an improvement in terms of distribution performance.
Budget
Almost all companies will have a budget plan, and this should include a breakdown of the logistics costs in appropriate detail – an activity budget. A traditional means of monitoring an operation is, therefore, to evaluate the cost of the logistics operation in relation to the expectations of the budget plan.
The budget approach has been developed in a variety of ways to enable more sophisticated and more meaningful measures to be created. The ‘activity’ concept means that the budget – and the respective measurement process – can identify and differentiate between functional activities (warehouse, transport, etc) and, more importantly, across core business-oriented activities. This might, for example, be by product group or by major customer, thus allowing for very detailed measurements reflecting the integrated nature of the logistics activities under scrutiny.
An additional development is the concept of flexible budgeting, which recognizes one of the key issues of monitoring – the need to be able to identify and take account of any changes in business volumes. This is particularly important in the logistics environment, where any reductions in volume throughput can lead to the underperformance of resources. The concept is based on the premise that budgets are put together with respect to a planned level of activity.
The fixed, semi-variable and variable costs appropriate to that level of activity are identified and form the basis of the budget. If activity levels fluctuate, then the planned budget is flexed to correspond with the new conditions. Thus, semi-variable and variable costs are adjusted for the change. In this way the change in cost relationships that results from a change in the level of activity is taken into account automatically, and any other differences between planned and actual cost performance can be identified as either performance or price changes.
This approach is particularly applicable to logistics activities, as there is very oft en a high fixed cost element, and any reduction in levels of activity can increase unit costs quite significantly. With a fixed (ie non-flexible) budget system it can be difficult to identify the essential reasons for a large variance. To what extent is there a controllable inefficiency in the system, and to what extent is there under utilization of resources due to falling activity? A typical example is the effect that a reduction in demand (throughput) can have on order picking performance and thus unit cost. A flexible budget will take account of the volume change and adjust the original budget accordingly.
An effective budget measurement system will incorporate the idea of variance analysis. In the context of logistics activities, variance analysis allows for the easier identification of problem areas as well as providing an indication of the extent of that variance, helping the decision process of whether or not management time should be assigned to solving that particular problem. As indicated earlier, an effective system will indicate if a variance has occurred, the extent of that variance and also why it has occurred with respect to performance/efficiency change or price/cost change (or a mixture of both). Variance analysis is best used within the context of a flexible budget, because the flexible budget automatically takes account of changes in activity.
It is worth noting that a good way to prepare for the monitoring of an agreed budget is to identify the largest cost areas and to concentrate on the regular review of these. Typically, in logistics, the largest cost element is labour, so this would be one key area to have effective measurement.
Engineered Standards
A number of companies use internally derived measures for certain logistics activities through
the development of engineered standards. This involves the identification of detailed measures for set tasks and operations. The means of determining these measures is a lengthy and oft en costly process involving the use of time and work study techniques.
When suitable and acceptable standards have been agreed for specific tasks, then a performance monitoring system can be adjusted to allow for direct measurement of actual performance against expected or planned performance. The advantage of using engineered standards is that each task is measured against an acceptable base. A monitoring system that measures against past experience alone may be able to identify improved (or reduced) performance, but it is always possible that the initial measure was not a particularly efficient performance on which to base subsequent comparisons.
Apart from cost, a potential drawback with engineered standards is that the initial time or work study data collection is difficult to verify. There is no certainty that an operative who is under scrutiny will perform naturally or realistically (whether consciously or subconsciously). Many logistics tasks do lend themselves to the application of engineered standards. Most warehousing activities fall into this category (goods receiving, pallet put-away, order picking, etc), as well as driver-related activities (vehicle loading, miles/kilometres travelled, fixed and variable unloading).
External Standards and Benchmarking
Another approach to cost and performance measurement is to make comparisons against industry norms. The intention here is that a company’s performance can be compared to similar external operations and standards, making comparison more realistic and therefore more valuable. For some industries, such as grocery retailing, these measures are fairly readily accessible through industry journals and associations. Examples of typical measures include order picking performance (cases per hour) and delivery cases per journey.
Some of the largest manufacturers and retailers that outsource to several different contractors use this concept to allow them to make detailed performance comparisons between the various depot operations. Thus they draw up ‘league tables’ of their depots based on their performance against an industry standard and comparing each depot and 3PL against the others. This can create a useful incentive for the different operations as they strive to maintain or improve their respective positions in the ‘league’.
Performance Tools and Techniques
Aside from balanced scorecards, SCOR models, and dashboards, other quantitative tools can be employed to measure supply chain performance. These tools include data envelopment analysis (DEA), analytic hierarchy process (AHP), and activity-based management. To elaborate, DEA is generally referred to as a linear programming (non-parametric) technique that converts multiple incommensurable inputs and outputs of each decision-making unit (DMU) into a scalar measure of operational efficiency, relative to its competing DMUs.
DMUs are collections of private firms, nonprofit organizations, departments, administrative units, and groups with the same (or similar) goals, functions, standards, and market segments. DEA is designed to identify the best-practice DMU without a priori knowledge of which inputs and outputs are most important in determining an efficiency measure (i.e., score) and assess the extent of inefficiency for all other DMUs that are not regarded as best-practice DMUs. Because DEA provides a relative measure, it will only differentiate the least efficient DMU from the set of all DMUs. Therefore, the best-practice (most efficient) DMU is rated as an efficiency score of 1, whereas all other less efficient DMUs are scored somewhere between 0 and 1.
AHP introduced by Saaty also can be used to measure the supply chain performance. AHP is a scoring method that was designed to synthesize the overall performance of the organization, while enabling the managers to make tradeoffs among different performance criteria. It helps managers to assess the overall performance of the company or its supply chain partners relative to their principal competitors. Activity-based management is a method of evaluating business performance using activity-based costing (ABC) that helps management discern value-adding activities from non-value-adding activities and then improve customer value and efficiency.
