November 17, 2020 Improving Manufacturing Project Forecasts

Project delivery dates are critical – and often wrong. Here’s how manufacturers can better manage the “when” of project completion.

The manufacturing process provides many challenges for project managers.

Project managers in manufacturing face constant pressure on delivery dates and getting those projections right in the face of various moving parts and shifting priorities can be a challenge. Manufacturing ­– from aerospace and automotive to chemical and pharmaceutical and everything in between – is essentially a series of sequential steps, so missed forecasts will have huge impacts, with any delays resulting in a cascading effect on many other parts of the process – and the organization. Conversely, accurate projections not only boost the bottom line, but they boost morale as well. People like certainty.

Accurate projections are challenging. From predicting resource availability to assessing dependencies, there’s a lot that can go wrong. The fact that the ongoing pandemic has forced more than 60% of employees to work remotely has significantly exacerbated that challenge, meaning project managers (and their teams) struggle. Even before the pandemic struck, a 2019 project management survey found only ​19 percent of organizations deliver successful projects​ most of the time. Manufacturers are no exception: despite an abundance of tools and dedicated project managers, organizations continue to fail to execute projects successfully.

Why are manufacturers struggling to complete projects on time?​ ​Conventional approaches to project management rely on a static plan that leaves no room for obstacles and bears little resemblance to projects in the real world. Most projects experience any number of setbacks — they face unexpected roadblocks, get sidelined for higher-ranked priorities, lose resources, switch project owners, or change course entirely. Traditional tools and trackers fail to account for the inevitable fluctuations that projects endure.

At a fundamental level, this boils down to the “when” of project delivery, and understanding both the roadblocks and the contributing factors is key to improving that all-important forecast. In particular, predicting the efficiency, conflicts, schedules, and availability of individual contributors is arguably the critical factor – and one of the hardest parts of a project manager’s job. These people are the resources that are expected to get the job done, and when they’re suddenly unavailable, delivery dates are inevitably missed.

Fortunately, some tools and techniques can help ensure project managers can accurately identify the “when” of project delivery. Let’s look at two examples:

Problem 1: Inconsistent Resource Availability

Traditional project management assumes the same workers will have the same availability for the project’s duration — but that isn’t realistic. Personnel resources can change in many ways: workers may get pulled into higher-priority projects, leave the company, or take time off, or their workload may vary by day or week. Typical complaints might be:

• we don’t know who is working on what
• we share resources but don’t know their availability
• we have to ask around to figure out who can take on new work

Without a way to track this information, you have no insight into where project bottlenecks are — or how you can solve them with available resources. The solution is functionality in newer project management tools known as resource-leveling. Rather than relying on a manual PM process, these tools consider availability and use AI and automation to identify under/over-capacity resources and automatically redistribute based on availability. This helps ensure that projects keep marching toward delivery despite fluctuations in resources.

Problem 2: Efficiency and Scheduling Conflicts

One of the most significant challenges of project management is effectively managing uncertainty. A delay of one small step can ruin the entire project schedule off course or lead to cost overrun. Yet these projects are built entirely around assumptions – in other words, guesses – that people make on how much they can get done in a given amount of time. And people are notoriously bad at estimating efficiency.

Sometimes workers underestimate their timelines because they don’t want to let down project stakeholders. Other times they are just wildly optimistic. The result is a struggle to meet deadlines, missing planned sprints because of unanticipated delays, or project schedules that are out of date almost immediately.

Newer project management tools again bring AI and automation to play to forecast scheduling and adjust timelines based on the system’s changes. This sort of predictive scheduling uses integrated time tracking programmatically to refresh estimates and schedules for greater project timeline accuracy. A “high confidence” estimate is provided, along with best- and worst-case plan estimates to allow for better preparation in the face of uncertainty, thereby mitigating risk.

No project manager or tool can hit every delivery date with 100% certainty.

But improved visibility on the accuracy of a project timeline and its constituent parts can go a long way to ensuring that other aspects of the manufacturing process stay aligned and on track.

Charles Seybold

Charles Seybold cofounded LiquidPlanner with a vision to transform online project management through innovation and improved design. For more than 10 years, he was a front-line software engineer at various startups before he moved into program management at Microsoft and, later, into portfolio and executive management at Expedia.com.

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