How Maturity Affects Portfolio Management

Application Portfolio Management helps you to identify where systems aren’t achieving technical and business goals. In previous posts I took a look at how to define those goals. We then investigated how to collect metrics that spot where goals aren’t met. We also looked at how goals and metrics are influenced by your role and level in an organization.

In this section, we’ll take a look at how portfolio management best practices are influenced by timing and the maturity of your organization’s decision-making processes.

How maturity affects goal definition

IT’s goals change based on the maturity of its planning. An architect may decide to boost the flexibility of several applications. This goal may come from his personal knowledge of a developer’s struggles with modifying a system. Goals at this level of maturity may be worthy and can generate results, but they are not necessarily aligned with corporate strategies.

In contrast, organizations with more mature planning will take a “top-down” approach to goal generation. They will start with general corporate principles and ensure that divisional and team goals support the overarching needs. For instance, a corporate goal may be to ensure that new product launches can be supported by IT within 2 weeks from submission.

Such a top-level goal would inspire subsidiary goals for different teams and roles. The architect may define his goal as reducing dependency levels and improving layering of applications. Development teams may set as their goals a specified turnaround time for change requests. Both goals are set in order to conform to the overarching strategy of boosting business flexibility.

The result of the more mature approach is that goals are aligned with higher priorities, lowering the likelihood of sub-optimal priorities. But also, it permits a more granular approach to managing goals. A CIO can spot where strategic goals are not being met, divisional heads can determine where these issues lie, and managers can locate root causes.

How maturity affects metrics collection

New goals are added or organized as your decision-making matures. This means that new and different metrics will need to be collected. In general, this simply means the same process as discussed previously where you follow a goal / question / metric approach. Though, now you may be doing it for more goals – or at least more coordinated goals.

There is another aspect to how maturity affects metrics collection. This relates to the quantity, timing, and kind of metrics that are collected. Let’s take a look:

• Quantity: An organization’s goal may be to reduce infrastructure costs for an application portfolio. In that case, a mature organization that wants exact results – or has already plucked the low-hanging fruit – will ask many questions to achieve the goal. “Which applications are duplicates?”, “Where is dead code?”, “Which applications cost the most to operate?”, “Which applications are most valuable?”. But for an organization that is just beginning the portfolio management process, a simpler set of questions can get you fast returns without the need for refinement. In that case, simply asking “which applications are duplicates?” may be sufficient.

• Timing: An organization with mature decision-making will likely investigate trends over time. For instance, monitoring the turnaround time on change requests for multiple development teams. A less mature organization will likely (often out of necessity) make decisions based on snapshot measures. Trending supports better decision-making, but again some decisions can be made based on less rich data sets. It will depend on the degree of accuracy required and risk-tolerance.

• Kinds of Metrics: Let’s look back at the three kinds of metrics sources for application portfolio management. They are surveys of stakeholders, data from related tooling, like ALM tools, and lastly data from the applications themselves, like complexity measures. To support a snap decision about which applications you should retire, you may rely on surveyed opinions only. Or, to determine where to re-factor an application you may harvest only code complexity data. To support a complex decision about which outsourcer to standardize on, you may need richer datasets that come from all three data types.

As your application portfolio management process develops you will see increased returns. Better decisions lead to lower waste and bigger business results. But critically, this doesn’t mean that value is low when you are starting your journey. In fact, it is the opposite. Returns generated by early decisions can be turned into reinvestment in improved business intelligence.

As your process matures you are always going to balance the projected returns versus the cost to collect the data. Taking an incremental approach and focusing on high-value goals early will help this process.