AI isn't Just for IT: 4 Ways Artificial Intelligence Powers Project Portfolio Management - Image by Gerd Altmann from PixabayOne of the most exciting emerging uses of AI technology is its applications in project portfolio management (PPM). PPM is crucial to the success of the project management office (PMO). In combination, businesses recognize their power to drive growth, increase organizational agility and deliver better business outcomes.

Many businesses have come to recognize the power of the PMO and PPM in driving growth, increasing organizational agility, and delivering better business outcomes. Certainly, the expectations of PMO performance have increased as businesses recognize their worth. Unfortunately, the PMO’s resources and budgets are not necessarily keeping pace with demands. One survey reports as many as 81% of portfolio management leaders report not having enough resources to meet demands. Today’s PMO is expected to do more with less, and they are expected to do it quicker.

While the PMO has a big job, it can be made easier with the implementation of PPM tools enhanced by AI capabilities. The applications of AI in PPM are broad and continuing to expand. This article highlights four specific ways AI in PPM can benefit the PMO and the business at large: risk mitigation, project selection, decision support, and business intelligence.

Mitigate Risk and Increase Successful Outcomes with Machine Learning

Machine learning is a powerful subset of AI that facilitates critical PPM capabilities, particularly in risk detection. In PPM, machine learning utilizes pattern recognition to examine an organization’s existing data to identify areas of risk long before they become bigger problems. This work is automated so that it can be done in the background with minimal human intervention. That’s good news for today’s overburdened PMOs, and it’s even better news for the companies they support.

Risk detection can avert project failure by identifying pain points ahead of time, allowing the PMO to prevent or mitigate damage. Stagnant projects can be identified and cut more quickly, minimizing wasted time and resources. Simultaneously, pattern recognition can also be used to identify positive trends and replicate and expand upon them. PMOs can use positive insights to increase the speed of project completion or enhance the overall agility of the project management process.

Leverage Predictive Analytics for Informed Project Selection

Just as machine learning can identify troubling trends, AI predictive analytics can prevent problems in the project selection process. Predictive analytics calculates the conditional probability of a potential event occurring based on historical data gleaned from similar events that have already occurred — following Bayes’ Theorem. This capability is a powerful tool for PMOs because it provides them an extrapolated if/then scenario model to drive project selection.

When a project is up for selection, predictive analytics can uncover constraints, bottlenecks, and other issues even before project selection. Algorithm-based scoring determines which projects will bring the most value to the business, which projects are small-but-easy wins, and which projects need to be avoided at all costs.

All of these factors are based on the organization’s data and predetermined scoring structure. It is automated and calculated in the background, freeing up the PMO team to focus on work that drives positive outcomes for the business. Additionally, predictive analytics help the PMO determine resource allocation, project hierarchy, and timelines after the project is selected but before launch. This early detection can move a project from “never” to “not right now” after the PMO assesses the predictive modeling.

Make Smarter Resourcing Decisions with Unbiased Data

PMOs’ decisions in allotting time, money, and resources to projects can have dramatic implications for the organizations they serve, both positive and negative. The challenge isn’t necessarily in the actual choice that needs to be made. It lies in the simple fact that PMO staff — and all others in the organization — are human beings, complete with biases and external environmental factors that can influence their decisions.

For example, a PMO might be ready with resources assigned to an ideal project that is queued up in the pipeline only to receive a visit from an executive demanding that a less lucrative pet project be fast-tracked to the front of the line. The PMO now faces a dilemma. Do they tell the person with more authority ‘no’ and risk the potential fall-out, or do they say yes, redirect resources and bump a project that actually delivers more value? The answer seems obvious, but the nuances surrounding the situation make it much more difficult.

AI helps PMOs make informed decisions that counter human bias, inter-office politics, and pet projects because AI doesn’t care about who will be most pleased (or displeased) by a decision. It computes the data against programmed parameters aligned with business goals and delivers options based on that data. This helps the PMO in several ways. First, it assures them they are making the best possible decision for the organization, absent of any human influence. Second, it provides the PMO with cold, clinical, and unbiased data to support their decisions when justifying them to outside parties who may prefer a different outcome.

Improve Business Acumen with AI-enhanced Reporting and Realization

Continuous improvement is key to growth and development, and it relies on an organization’s ability to assess and reassess its processes and functionality constantly. AI helps the PMO harness an enormous amount of data and turn it into comprehensive reporting that drives informed decision-making. AI equips the PMO with the business intelligence needed to place the right bets at the right time, using the right resources to complete the mission. It streamlines data integration and automates tedious tasks like KPI monitoring, data collection, and report generation, limiting potential errors and easing constraints on the PMO’s busy schedule.

More importantly, AI-enabled reporting provides the executive team and key stakeholders with the data they need to drive strategic decision-making and reaffirm the competency of the PMO. With the insights gained, all parties can work together to develop a valuable, business-centric portfolio.

Conclusion

There’s no question that today’s PMOs are facing unprecedented demands on their time and capabilities. At the same time, the resources they need to execute those demands diminish and the margin for error has virtually disappeared. AI is the key to unlocking the PMO’s potential as a valuable partner. It will provide vital support as PMO professionals do their part in achieving business goals.


KeyedInAt KeyedIn, our mission is to make our customers more successful by empowering them to place the right bets, turn quickly and deliver faster. As a leader in Agile Portfolio Management, KeyedIn offers a suite of SaaS solutions that support business transformation, strategy realization and organizational change. The company’s award-winning products go beyond simple project management to encompass portfolio analysis, scenario modeling, capacity planning, product management, strategic resource management and more – supporting the evolving needs of PMOs, ePMOs and SROs. Join the hundreds of customers that have partnered with KeyedIn, including Walgreens Boots Alliance, Universal Electronics and Office Depot. Learn more by visiting www.keyedin.com.

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