Five Best Practices for Calculating PPM Tool ROI

 Illustration image of the Sciforma Blog article on 5 best practices for calculating the return on investment of your PPM tool

Many organizations prepare an ROI analysis with or without their prospective vendor’s help and then take the results with a grain of salt. Here are some practices which may help you better position the role of ROI analyses in your decision-making process and increase your confidence in the results.

 

1. Put ROI Calculations into Perspective

First, it’s important to keep the ROI exercise in perspective as part of your go/no go investment decision-making framework. ROI calculations are estimates and should be used as much to test the rigor of the business case your vendor is putting forward and the strength of its value proposition, as it is to make actual financial projections.

Further, impressive ROIs are no guarantee of success. For example, if you haven’t identified a strong executive sponsor and champion, your ROI calculation will not matter. Finally, ROI calculations will never be revisited a year or two from now to validate or invalidate their accuracy. So, understand it is a step in a process that is valid for a moment in time.

In sum, ROI is an important component of an investment decision that should be in made in consideration with several technology investment risk factors. They include the level of internal executive support, your vendor’s track record of successful deployments, and your PPM process maturity level.

 

2. Ensure Alignment between Your Model, Expected Tool Benefits, and Strategy

Some ROI models are generic and disconnected from the solution and its specific capabilities that portend to drive quantifiable financial impacts. It is important to understand your selected tool’s solution value proposition in order to provide a context and a framework for evaluating its ROI and gear your ROI analysis on monetizing these benefits.

Also, if you’re at the point in you buying journey where ROI evaluation is of interest, it is assumed that you have first identified key pain points that your PPM tool is intended to address and that you have aligned these pain points with your PMO objectives and KPIs. It is also assumed that there is a direct line of sight between these objectives and KPIs and your key C-level objectives such as profitable growth and long-term competitiveness.

In other words, if the quantifiable benefits you expect from your tool are not aligned with your PMO and broader strategic objectives, your analysis is complete; your expected ROI is zero.

 

3. Incorporate Risk

To calculate the ROI of any technology investment, companies need to consider not only benefits and costs, but potential risks. Incorporating risks at various levels of the calculation can be used to develop best guess, worst-case and best-case scenarios.

There are three levels of investment risk. The first is the risk of a successful implementation (on-time, on budget, on scope). The second is the risk of a successful roll-out from an organizational change management perspective (i.e. user acceptance and adoption). The third is the risk of not achieving the desired ROI.

The best way to mitigate the implementation and roll-out risks is to partner with a vendor with a track record of successful deployments.

There are several ways to mitigate the risk of achieving the desired ROI. They include:

  • Providing conservative inputs for each of the benefit levers which call for a percentage improvement guesstimate.

  • Creating worst-case, best-guess, and best-case scenario estimates.

  • Including only high-confidence benefits in your calculation (e.g. hard savings based on internal measurements or trusted third-party analysis).

  • Including “soft” benefits (i.e. benefits that are real but difficult to measure) in your business case but keeping them separate from the ROI calculation.

 

4. Considering Focusing on Hard Savings

PPM ROI models that go beyond PPM process savings to include revenue impact (e.g. revenue-generating projects) require accounting for the timing and duration of post-project delivery project benefits, and additional layers of assumptions and estimates. For example, decreases in project cycle times result in faster access to that revenue. Valuing that as well as the value of the ensuing chain of projects in the pipeline that can start sooner, can result in a model that is so complex that it defeats its intended purpose as a tool for building investment decision clarity and confidence.

It is much easier to develop baseline and improvement estimates for cost savings then it is to assess and forecast revenue impact, operational cost savings, the value of improved customer service or loyalty, or time-to-marked improvements. As a result, if you can justify your investment based on cost savings alone, you won’t have to deal with the model complexity risks which may lower the confidence in your calculations.

Fortunately, IT PPM benefits can be largely described as savings from productivity/efficiency gains associated with the planning and execution of projects. And since IT PPM represents the starting point for most PPM implementations, it is assumed that this practice tip has broadly applies to readers of this post.

Further, savings from better project planning and execution apply to all project types. As a result, this ROI calculation can be used as a conservative, minimum ROI estimate. As such, it may be enough to justify the investment without considering the operational impact of projects (i.e. benefits that accrue after the project has been completed such as the effects of better time to market or improved operational process efficiencies).

 

5. Document Your Scenario Assumptions, Parameters, Inputs & Outputs

Calculating ROI is a simple mechanical operation which is literally done with the push of a button. The important and sophisticated work is in identifying the model assumptions/parameters, inputs and desired outputs. Making these assumptions and variables clear and transparent makes it easy for everybody to get a quick sense of the robustness and quality of the logic and thought process behind the model. These factors set the baseline which can be used to compare alternative solutions. A comprehensive list of potential assumptions/parameters, inputs and outputs can be found in the Sciforma ROI Calculator White paper.

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