FinTechAutomationHarnessing the Business Value of IT Investments in the Electronic Order-to-pay Process

Harnessing the Business Value of IT Investments in the Electronic Order-to-pay Process

During a recent study, we developed an evaluation tool that visualises the mechanisms of value creation in the electronic order-to-payment cycle. A three-stage metrics model was created, dividing the order-to-payment process into e-ordering, e-invoicing, and e-payment. Our task was to gather up information and build a structured set of performance indicators, a template for quantitative measurement that can be used in organisations operating in different industries. Following this introduction, we first discuss the main uses of the measurement tool. Then, we present the findings from three case studies. We conclude by listing the concrete steps companies should take when using the measurement tool.

Using the Model – How and Why

The model offers a set of measures for evaluating the impacts of process automation. To use the model, the user organisation should, first, select the metrics that are suitable for each of the measures. For example, the measure ‘number of processing errors’ could be measured by the metric ‘number of user error reports’, by the metric ‘number of complaints from suppliers’ or by some other proxy metric. We suggest that these ‘how to measure’ decisions should be based on company-specific knowledge. The study offers guidelines for evaluation i.e. helps to answer the question ‘what to measure’. A second task is to detect the availability of the required data. For example, ERP-data can be used to evaluate inventory turns, accounting figures to calculate handling costs, and user estimates to quantify some ‘hard to measure’ effects, such as user satisfaction. In the ideal situation, all data could be directly drawn from company information systems. However, in reality, some of the data still has to be collected more or less manually.

There are two main functions of our evaluation tool. Firstly, the model can be used to support decision-making in IT investments. By comparing the potential benefits (e.g. cost savings and additional revenues) to investment costs, the user organisation can make reasoned decisions regarding the implementation of new technologies. For doing this, all potential payoffs must be evaluated. The chosen measures should be finally given uniform, financial values. Costs should be easy to calculate in monetary terms, whereas revenues might require some effort. Some asset-side impacts could also be transformed into monetary values, e.g. by measuring the opportunity cost of excess cash on company accounts, which basically equals the return of an alternative investment.

Secondly, management can use the evaluation tool to monitor higher-level aggregate measures from top-down on an ‘order-to-pay dashboard’. For these process-monitoring purposes, the company could use percentage values which are comparable and easy to interpret. They should, however, first calculate how business performance adjusts to certain percentage changes, to be able to set proper goals and tolerances for the performance indicators. For example, it could be estimated that a 5% improvement in on-time delivery will result in 2% increase in sales.

Findings from Case Studies

To test the proposed framework, we conducted an in-depth case study at Marimekko, a Finnish design company, as well as in two supplementary case companies. We found that the motives for automating order-to-payment relate closely to cost avoidance. Once applications were implemented, however, the focus and post-auditing efforts were directed particularly towards better asset utilisation. Potential revenue-creating effects were reported as well, yet it was concluded that they are particularly difficult to observe and measure. The case results also indicated the importance of system integration within the order-to-payment process.

In addition to the case study from Marimekko, we tested the model in two supplementary case companies. Cost-related effects were repeatedly emphasised which further supports the argument about impacts of automating order-to-payment cycles being cost-centric. However, the message was that once applications were implemented, challenges and post-auditing efforts related closely to better asset utilisation. As a comparison, a retailing company reported that the share of e-orders in direct buying is already close to 100%, whereas current challenges relate to digitising and centralising indirect purchases. Concerning the e-invoice indicators, enhancing the efficiency of the e-invoice ‘approval loop’ was considered as a major challenge in all case companies.

Recommendations

What are the concrete steps a company should take when applying the measurement tool? Here are eight that we recommend:

  1. Choose the measures to be used and identify metrics that best indicate performance in these dimensions.
  2. Categorise the measures according to importance from the user organisation’s point of view.
  3. Draw ‘critical paths’ between different level measures i.e. pinpoint mechanisms of business value creation.
  4. Gather the data (duration of this phase largely depends on how the data can be directly drawn from information systems).
  5. Formulate uniform financial values to the process level measures as far as possible.
  6. Evaluate EVA i.e. business performance in relation to the capital employed (can be used as justification for IT investments).
  7. Evaluate how business performance changes when process level variables change by some percentage value.
  8. Set targets and tolerances for the variables and monitor process level measures regularly by comparing how well the ‘order-to-payment machine’ performs in relation to previous periods (e.g. monthly reporting).

About the Study

This study is a part of Heikki Lempinen’s MSc thesis at the Helsinki School of Economics (HSE), published in February 2009. The study was carried out in the Real-Time Economy (RTE) programme, which is a joint project between HSE and Tieto focusing on electronic financial services. You can find the thesis and the full model from the RTE site at www.hse.fi/rte.

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