The AlixPartners A&D Minute
Back to basics on program management, the latest AlixPartners point of view on program management, was published in October 2023. Since then, the geopolitical landscape has shifted significantly. Conflict permeates the Middle East, the war in Ukraine has intensified, and the risk of conflict in Asia Pacific remains elevated. In this environment, warfighters increasingly rely on the defense industrial base.
Getting the right weapon system to the right place at the right time is critical. The importance of defense program management—a competency we outlined in great detail in October 2023—remains paramount. Much has changed since then, including further degradation of Estimate at Completion (EAC) results, amplifying the need for a more focused look at the topic.
EACs: The more things change, the more they stay the same
EACs are influenced by supply chain bottlenecks, material price inflation, the lingering aftermath of the pandemic, and other factors. However, as we pointed out in Back to basics on program management, the root causes of the negative charges may stem from weaknesses in program management fundamentals.
Today, major defense primes' adjustments continue to exert downward pressure on margins, even as they recover from significant negative adjustments in the past. Notably, net-positive EAC adjustments are declining year-over-year.
Regular EAC charges expose systemic challenges that need to be resolved. As charges from past years continue to filter through to financial results, it becomes increasingly evident that bad program management habits are challenging to unlearn.
Digging to the root cause
EAC results only tell part of the story. We surveyed dozens of global program management experts to broaden our perspective on top challenges they face today.
Below is an analysis of the Top 5 drivers for successful program management.
- Talent management
Program managers (PMs) should be hired based on the strength of a specialized skillset that goes beyond traditional technical expertise. Talent will only get you so far. Cross-functional capabilities are necessary as talent management plans must be intentional and structured around a core set of program management competencies.
Tailored talent development planning must be instilled to further transform experience into expertise. The first step is establishing a baseline set of PM competencies across your program organization, identifying opportunities to align resources toward addressing gaps. Secondly, creating leadership rotational training programs provides current and future PMs exposure to necessary disciplines. A PM who has only worked in engineering is rarely the most efficient leader, especially when compared to an engineer who has worked in supply chain, manufacturing, customer support and business development. In large development programs, a key role that can improve program management effectiveness is the position of an "architect," working side-by-side with the PM. The architect is typically someone with a very experienced technical background who can challenge and deal with overall system performance and technical compromises. Many of the best program managers AlixPartners has worked with bring to bear this diverse experience, along with strong leadership and expertise in fostering continuous collaboration throughout the organization.
- Real time data visibility and analytical tools
PMs are often overwhelmed by manual data management, struggling to turn disparate data sources into actionable insights for sound decision making. As a starting point, harmonizing disparate data sources into a single, organization-wide taxonomy creates efficiencies, reduces manual labor, and allows more time to focus on deeper value-add insights. A single source of data and standardized analytics leads to real-time access to metrics and objective reporting with greater accuracy, driving better customer and business outcomes.
- Sales, inventory, and operations planning (SIOP)
Supply chain management is an overwhelmingly manual, resource-heavy process. Massive amounts of data and analysis are necessary to improve supplier performance tracking and to better forecast lead times and delivery. Connecting and digitizing both internal and external sources of quantitative and qualitative data enables a more comprehensive view of the supply chain. This includes better visibility into performance metrics and market factors that may be impacting availability of materials and parts, resulting in more thorough and responsive supplier risk management.
As supply chains face increasing internal and external pressures, effective SIOP management has never been more important for enhancing supply chain resilience. A key focus for CEOs and supply chain leaders is optimizing production, maintenance, and sustainment capacity, while being able to react quickly to disruptions. One core tenet of building supply chain resilience is maintaining full chain-of-custody fidelity. OEMs are on the hook to ensure parts are not only fit for purpose and produced efficiently, but also meet regulatory requirements while safeguarding operational security. Better use of data in SIOP can streamline these processes, helping organizations respond more quickly to challenges and fortify their supply chain resilience, especially in contested environments.
- Program planning and execution
Too many programs spend the entire execution lifecycle trying to catch up to plan. This is often because the necessary structural elements are not in place at time of kickoff. To achieve "green-from-day-one" program readiness requires standardized pre-execution workflows and frameworks to ensure everything is in place at kickoff.
To be sure, every program encounters unique circumstances, but generalized practices can be utilized to ensure governance frameworks and adequate resources are in place at the outset. The more thoughtfully that pre-execution planning is orchestrated, the more effective the program management plan, risk and opportunity management plan, and others will be.
- Estimating and baselining
Program estimating and baselining are also critical. This starts from an executable basis of estimate (BOE), combining historical and forward-looking performance data. BOEs need to be adjusted for projected rate and market fluctuations, and then validated by technical expertise across all functions. Objective reviews of estimates and baselines are a final check on reasonableness and readiness of the proposed solution before finalizing.
This process must be standardized across the enterprise with centralized governance policies to ensure that every program is baselined with the same discipline and rigor, resulting in a comprehensive work and organizational breakdown structure that entirely captures program requirements and enables efficient execution of scope.
Set aside AI hype. Focus on AI performance
There is no silver bullet to solve all these problems. However, effective decision-making and strong leadership goes a long way. Artificial intelligence can help PMs make better decisions that positively impact customers and warfighters. However, AI faces its own set of challenges.
Assume certain foundational elements required to use most AI tools at scale with your data, including aggregation and generative-AI usability, are solved. Questions concerning how to capitalize on this investment in AI and how to apply it to PMs' challenges remain. How do you rapidly move along the learning curve from descriptive analytics for anomaly detection, hypothesis testing, and pattern mining to more predictive capabilities? Answering this is necessary to expand into prescriptive techniques to leverage for proposals and BoEs before a program is ever awarded. The goal is to avoid structural deficiencies in the bid phase that won't be solved by performance alone.
A potential use case that highlights the value of developing AI for program management is improving cost estimation models. For example, vendor classification in cost estimation can be challenging, particularly when data on smaller vendors is opaque. However, by training an AI agent to map these entities to their parent companies, we can often gain a clearer understanding of whether cost increases presented during negotiations reflect actual challenges the vendors face. Incorporating additional data sources – for example – raw material and labor data can further be used to refine the assessment of whether proposed cost increases are justified and can also be a baseline for forecasting future cost growth. Then, analyzing the performance and pricing history of similar suppliers can provide even greater insight into whether the issue is sector-wide or specific to the vendor. The evolution of AI in program management can be directed to solve a wide variety of program management hurdles and improve bid competitiveness, but aligning AI capabilities with an organization's most critical needs is a path each company must chart for itself.
Upskilling at scale
AI can also help bridge the talent gap, initially providing every PM with the equivalent of a capable junior analytical resource who needs concrete direction. It can then evolve into an advisor role who can provide proactive, objective, quantitative support and foresight with less bias than a PM who may aim to please a customer. It also can ensure at a minimum all PMs, CAMs, and finance support ask the right questions to drive action.
Poised for success
Defense companies want to ensure AI investment empowers program managers, control account managers, and others on the front lines running a program, rather than simply be a buzzword. Armed with the right tools and insights, tied into live performance metrics, program managers will likely see more time and energy for proactively managing programs rather than simply reporting on them.
The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.
