Portfolio Optimization—Data and Constraints


In our hyper-accelerated business world, data analysis and data visualization are exceptionally important. In the realm of project portfolio management (PPM) and PMO’s, organizations need robust data analysis to strengthen decision making and improve strategic execution. The key is to have the right processes in place to collect the right data and ensure that the data is of good quality. As I have said before, data collection is not free; any data that is collected but not actively used is a waste of organizational resources. Knowing what information is needed to drive better decision making will help ensure that only important data is collected. Therefore, organizations should wisely consider what metrics, analytics, and reports are most important to senior leaders and then develop or improve the processes that drive the collection of that data. The power of having good portfolio data is to conduct strong portfolio optimization.

3 LEVELS OF ANALYSIS

Once organizations have a stable foundation for PMO/PPM data collection, they can embark on the data analysis journey. The graphic below highlights three levels of data analysis:

  • Descriptive analysis—this helps answer the basic “what has happened?” This level of analysis is the most basic as it is fact-based and is required for developing key performance indicators and dashboards.
  • Predictive analysis—this helps answer a more important question, “what will happen?” With sufficient data, organizations can begin to predict outcomes, especially related to project risk and project performance and the impact to project delivery as well as the portfolio as a whole.
  • Prescriptive analysis—this helps answer a more difficult question “what should we do?” This requires more detailed and advanced analysis to determine the optimal path against a set of potential choices. Prescriptive analysis of the portfolio provides significant benefits by enabling organizations to choose the highest value portfolio and choose a group of projects with a higher likelihood of success.

pmo-analytic-capabilities

 

PORTFOLIO OPTIMIZATION

Portfolio optimization is major part of the prescriptive analysis described above. Organizations should endeavor to get to this point because it delivers substantial value and significantly improve strategic execution. In order to optimize any part of the portfolio, organizations must understand the constraints that exist (e.g. budgetary, resource availability, etc.). These constraints are the limiting factors that enable optimal scenarios to be produced. There are four basic types of portfolio optimization described below:

  1. Cost-Value Optimization: this is the most popular type of portfolio optimization and utilizes efficient frontier analysis. The basic constraint of cost-value optimization is the portfolio budget.
  2. Resource Optimization: this is another popular way of optimizing the portfolio, and utilizes capacity management analysis. The basic constraint of resource optimization is human resource availability.
  3. Schedule Optimization: this type of optimization is associated with project sequencing, which relates to project interdependencies. The basic constraints of schedule optimization are project timing and project dependencies.
  4. Work Type Optimization: this is a lesser known way of optimizing the portfolio, but corresponds to a more common term, portfolio balancing. The basic constraints of work-type optimization are categorical designations.

APPROACH

The following diagram summarizes the above points and highlights how having the right data inputs combined with constraints and other strategic criteria can produce optimial outputs across four dimensions of portfolio optimization.

PMO Analytic Framework for Portfolio Optimization

Point B Consulting’s 5-step methodology for conducting PMO analytics enables organizations to realize the full potential of their analytic processes.

  • Define: Determine the performance criteria for measuring PMO/PPM success and develop a set of questions / hypotheses for further modeling and investigation
  • Transform: Gather and transform all available resource, project, business data for further visualization and analysis
  • Visualize: Inventory all projects with related resources and highlight key trends/insights based on project and business data
  • Evaluate: Develop analytic framework to test, adjust, and optimize against tradeoffs between project sequencing, resource allocation, and portfolio value
  • Recommend: Develop a final set of project prioritization recommendations for desired future state

 

In summary, portfolio optimization delivers significant strategic benefits to any organization, but getting the right processes in place to collect good data is not easy. Having the right data can enable your organization to know what is happening to the portfolio (descriptive analysis), what could happen (predictive analysis), and what senior leaders should do (prescriptive analysis).

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Five Uses of a Prioritization Scoring Model


Project prioritization is one of the most common topics in portfolio management literature. Within the context of project prioritization is the matter of scoring models because scoring models are the most widely used approach to prioritize projects. Although there are a lot of opinions on the effectiveness of common scoring models, they are nonetheless the most common method for prioritizing projects. However, most people may not realize the many uses of a scoring model and how it drives better decision making beyond project prioritization. In this post, we will look at five uses of a scoring model.

1) Project prioritization is the most common reason for using scoring models. As we saw in a previous post, project prioritization is for resource allocation. Since portfolio management is about delivering the most business value through projects, it is logical to ensure that resources are spent on the most important work. Ranking projects helps provide a common understanding of what is most important in the organization and scoring models are one of the easiest ways of establishing a rank order. For more information on using prioritization scoring models to rank order projects, please see Mastering Project Portfolio Management.

2) A prioritization scoring model is also used for project selection. The idea is to rank projects from highest value to lowest value and select projects until resources run out. This approach has merits over other approaches that do not sufficiently take account of strategic drivers. However, it can be shown that even simple optimization techniques can yield a higher value portfolio at the same cost. For organizations that do not employ portfolio optimization techniques, using a scoring model to rank order projects and fund projects until resources runs out is a reasonable way to go.

3) Portfolio optimization is very useful for identifying higher-value portfolios than merely using scoring models as discussed in the previous paragraph. The scores for each project can represent a “utility score” which can then be used as the input for the optimization calculations. In this way, projects are optimized based on all the scoring inputs, not merely on net present value or some other financial estimate. For more information about this technique, please refer to Richard Bayney’s book Enterprise Project Portfolio Management: Building Competencies for R&D and IT Investment Success.

Efficient Frontier Example

4) A prioritization scoring model can also be used to make go/no-go decisions at gate review meetings. There are at least two ways to accomplish this:

A) Organizations can predetermine a threshold score that projects must exceed in order to be considered for inclusion in the portfolio (known as a scoring hurdle).

B) An alternative approach is to use a scoring range to provide better input to the decision makers. In other words, if the scoring range were from 0 to 100, scores below 30 might represent high-risk/low-value investments that should otherwise be rejected, but may only get approved if there were other intangible factors not considered by the scoring model. Projects in the middle range of scores might be approved with more scrutiny, and projects in the upper range would likely get approved. The prerequisite to taking this approach is to have an adequate number of historical scores from past projects to compare against. Statistical analysis would further help refine this approach. Another assumption is that the scoring model would have to remain fairly consistent over time with few changes. Otherwise, historical scores could not be used to determine the correct range unless special adjustments are made to the scores.

5) Finally, scoring models provide the input to build risk-value bubble charts, which provide great visual information to senior leaders. The scoring model needs to contain both value elements and risk elements as inputs for the diagram. Normally, these scores are summed to become a single number, but with the risk-value bubble chart, we need to break out the total value score and the total risk score in order to correctly plot the data on a chart. With further data elements such as strategic alignment and expected cost (or return), more information can be displayed on the bubble charts (see example below).

Portfolio Bubble Chart

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The Purpose and Goal of Prioritization


Prioritization is about focus—where to assign resources and when to start the work. It is not about scoring methods and ranking mechanisms.  Without defining project priorities, it is difficult to effectively distribute personnel to carry out the highest valued projects. Project priorities enable management to assign their employees to the most important projects. Gaylord Wahl of Point B says that priorities create a ‘true north’ which establishes a common understanding of what is important. Prioritizing projects enables organizations to make the best use of company resources. Without a clear and shared picture of what matters most, lower-value projects can move forward at the expense of high-value projects. Again, prioritization is about focus—WHERE to assign resources and WHEN to start the work. Prioritization and resource allocation go hand in hand.

Resource Priority and Schedule Priority

In the diagram above we see that prioritization relates to resource priority and schedule priority. Resource priority drives the question, “where are we going to invest our resources now?” The fundamental resources are money and people. Since there is often more work to be done than there are resources available, senior leadership needs to provide guidance of where to investment money and where to allocate human resources.  This requires an understanding of how to get the most important work done within existing capacity constraints. However, not all projects can be initiated immediately. Prioritization can also help direct the timing and sequencing of projects. In some cases, high priority projects may have other dependencies or resource constraints that require a start date in the future. In other cases, lower priority projects get pushed out into the future. In both cases, schedule priority helps answer the question “when can we start project work?”   Having the right human resources available to do project work is a critical success factor. High priority projects have a higher likelihood of success due to adequate staffing. Lower priority projects may face more resource contention and have a higher risk of project delays due to inadequate resource time. Lower priority projects that get pushed out into the future have an even lower likelihood of success since these projects face challenges around project initiation and higher resource contention.

The purpose of prioritization is to allocate resources to the most important work. Prioritization provides focus—WHERE to assign resources and WHEN to start the work. The goal of prioritization is to accomplish the most important work to deliver maximum business value. Although prioritization is a critical need in many organizations, in the next post we will highlight cases where prioritization is a waste of time.

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Prioritization Matrix


In a recent LinkedIn discussion, questions were asked about the short-comings of prioritization matrices. I would like to highlight the strengths and weaknesses of using such a tool for portfolio management. Firstly, a prioritization matrix differs from a more traditional scoring approach in that it offers a limited number of priority selections. The most simplistic prioritization matrix has three choices, low, medium, and high. Of course, to be effective, every choice should have some predefined criteria. Otherwise, the matrix is of little value because decision makers can have wildly different views for what is of high importance versus low importance.

Strengths
Prioritization matrices have three primary strengths: simplicity, speed, and applicability to all types of work. Prioritization matrices are easy to understand and simple to use. Calculations are not required for determining the relative priority of a project. Basic criteria should be developed for each part of the matrix, but once complete, decision makers can apply the criteria to various types of work. Because of its simplicity, prioritization becomes a much faster exercise and allows decision makers to quickly distinguish important projects from less important projects. In addition, various kinds of work can be prioritized using a prioritization matrix. With a traditional scoring model, it is difficult to evaluate “keep the lights on” type of work, but with a prioritization matrix it is easier to compare priorities for project and non-project work.

Weaknesses
Prioritization matrices are unable to produce a rank ordered list of projects in a portfolio. At best, such a matrix can provide a categorical ranking of projects in the portfolio, but this won’t help prioritize projects within the same category. Prioritization matrices cannot do a good job of evaluating projects based on multiple criteria, and therefore cannot do a thorough job of distinguishing important projects from less important projects. When evaluating multiple large projects, a scoring system will provide a more accurate analysis over a prioritization matrix.

When Should a Prioritization Matrix Be Used?
Prioritization matrices are good for organizations new to the portfolio management process. Due to the simplicity, organizations can quickly get the benefit of prioritization without spending the time to do a thorough scoring of each project. Even in organizations where projects are scored and ranked, prioritization matrices can be used for “pre-screening” purposes to do a preliminary prioritization. This would be commonly used in a stage-gate process before a formal business case has been developed. A governance team could quickly determine a categorical priority for the project at an early gate review. Prioritization matrices can also be used to triage large volumes of project requests to focus the organization on the hottest projects. I have seen this approach used in an organization that received a high volume of small project requests. In this case, scoring would be an over-kill; the organization just needed to determine the most important work at that time.

Priority Matrix Sample

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