Improving Your PPM Situation
Portfolios are not created in a vacuum. When you create a portfolio you select
from a set of proposals while striving to realize corporate goals. Subsequently,
your company's project management capabilities determine how well your portfolio
is executed. You should think of PPM as a set of PPM decisions (project
selection and resource allocation) that occur within the context of a PPM situation
(existing proposals, strategic goals and project management capabilities). Much
of the PPM literature, education and practices focus on PPM decisions. The field
gives scant attention to improving PPM situations. However, improving your PPM
situation may be the best way to create value. For example, the value created
by improving your proposal processes, thereby providing you with better choices,
may exceed the value created by improving your project selection.
PPM is not just about portfolio creation.
Executives must improve all the business processes that
affect their portfolios.
Feedback from PPM results can help you improve your PPM situation. The new
model provides metrics that will help you evaluate and improve your proposal processes
(to raise  )
and your project evaluations (to improve prioritization and  ).
These improvements will relax the aforementioned trade-off between strategic and
financial goals. You will be able to fund more projects while maintaining a high
ROI for your portfolio.
Improving Prioritization and Project Evaluation
Figure 11 estimates the benefits of improving prioritization.
For the same strategic bucket, it shows the NPVs available from your current prioritization
and the NPVs that would be available from an improved prioritization.
With better prioritization you can select more proposals
and still achieve your financial goals.
Figure 11: How the quality of prioritization affects a buckets financial prospects
If you evaluate projects with a scoring model, PPM results can help you improve
your model, and thus your prioritization. By analyzing PPM results, you can set
your model's attribute weights to maximize the model's ability to distinguish
Good from Bad projects. Likewise, you can set the weights to maximize the correlation
between proposal scores and the value created by projects.
Furthermore, if an optimal weight is small, that attribute is not helping you
select proposals. Either you are evaluating the attribute poorly or the attribute's
scale is faulty. In the first case, you must invest in resolving more uncertainty
during the proposal process. In the second case, you must fix the attribute scale.
Scoring models differ from financial metrics and decision analysis models.
Scoring models make predictions based on statistical relationships, analogous
to linear regression. Financial metrics and decision analysis models are physics
models. Presumably, PPM results can help you improve these models as well. For
example, by analyzing PPM results you might estimate the accuracy and precision
of key variables in your model. These estimates will identify aspects of the model
that need improvement.
Improving Proposal Processes
In addition to improving your evaluations, you can improve your PPM situation
by developing your proposal processes. This strategy is often overlooked in PPM,
but better proposal processes will raise
and create value.
Histograms of project scores will help you evaluate and improve your proposal
processes. Figure 12 illustrates histograms for incremental
innovations (left) and for major innovations (right). Each histogram shows the
number of proposals having each score, the average score (solid vertical line),
the cutoff value used to select projects (dashed vertical line) and the variance
of the proposal scores.
Figure 12: Histograms of proposal scores
Incremental innovations face less uncertainty (than major innovation), so proposal
processes should consistently produce good ideas. As a result, a histogram of
proposal scores should have a high average score and a small variance (left hand
Figure). If the histogram has a low average, you must improve your proposal processes.
These improvements will raise the average score, shift the histogram to the right
and raise .
Major innovations face greater uncertainty, so few ideas will succeed. This
is all right. When pursuing major innovations, asking for consistently good ideas
is asking for failure. Because some ideas are poor ones, the histogram for major
innovations has a low average and a high variance. If it has a high average, you
must inspire and challenge your managers and staff to be bolder. Importantly,
because some ideas will be poor ones, you cannot raise the of major innovations
by increasing the average score. Instead, you must raise the
variance. Greater variation will extend the right tail of the distribution, raising
.
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Management
