The last twelve years of helping R&D teams overcome the challenges of portfolio management has taught us a lot about strategic resource planning. We’ve watched R&D-driven firms spend millions of dollars on complex project management systems, hoping for a magic wand that properly staffs R&D projects and ensures their timely and efficient completion. We’ve seen companies deploy systems that compile project schedules with staff and budget needs, systems that track time and money spent on each project, and processes that authorize projects and the resources they require.
Yet despite substantial investments in these systems, adequate staffing remains an elusive goal for many companies, and their projects are delayed when appropriate staff or facilities become unavailable at key points in development. This is what I call resource planning’s “last mile” problem, falling short of delivering the promised results despite extraordinary investment.*
At many organizations it is still devilishly difficult to answer the following questions:
- What work cannot be completed on-time with current staff?
- How many more staff are needed, and in what roles?
- Can all highest value activities be completed without delay?
- What value is lost from current project delays?
- What is the cost of under-utilized staff?
Working with dozens of clients and hundreds of project management staff over the years, we’ve identified eight challenges that confound traditional resource planning software and processes:
- Supply and demand data are maintained in disparate systems
- Matching supply and demand at too high a level
- No tools to deftly manage all the details within the supply and demand data hierarchies
- Lack of role pooling for fungible resources
- Using unrealistic utilization rates
- Ignoring the inevitability of project delays
- Lack of scenario analysis capability to compare myriad staffing and project scheduling options
- Inability to extrapolate from current demand to inform medium- and long-term staffing plans
Fortunately, the solution is not to reject the systems already in place—after all, they are properly collecting and storing important information about the organization in real time—but rather to address these failures with a targeted set of purpose-driven tools and adjustments to processes. In this blog post, I give a rundown on each of the challenges, and discuss the process- and tool-based solutions for surmounting them. Whether you decide to employ the Enrich Analytics Platform to bridge the last mile at your firm, or address these issues on your own, I hope you find the following insights helpful! If you’re interested in learning more about how the Enrich Analytics Platform can enable best-practice resource planning, please drop us a line.
Supply is from Mars and Demand is from Venus
In many firms the staff roster and hiring plan is owned by human resources, while the demand is curated by the project management office or R&D. Two departments + two databases = at least two, and sometimes more, inventories of staff roles. In many firms we visit, this is the number one roadblock to answering the questions above. Lacking a tool to map and resolve the linkages between supply and demand sends many teams to Excel, which is unfortunate, because Excel is ill-suited for the mapping task, as well as the constraint analysis, optimization and scenario analysis that are required for proper resource planning. Using Excel also means you’ll probably need to relive the pain of mapping supply to demand every time new data comes in.
The Enrich Analytics Platform includes a mapping module, where supply and demand can be mapped directly, or to intermediate roles to allow pooling when appropriate (see “Some Roles are Interchangeable…” below).
The View from the Mountain-Top: Always Scenic
In the face of the mapping challenges identified above, some firms simply look at the overall number of people required (say, by department) to complete the current project load, and become complacent when the numbers align. The problem is that general alignment between staff supply and project demand at a high level may disguise a skills gap with respect to specific roles. At one pharmaceutical firm we spoke with, the project management office felt alignment was good, with projects’ requiring only 3% more staff than was currently available. Yet when management drilled down into the details, they found that specific roles were under or over-subscribed by more than 50%; at the department and organization levels, these gaps were cancelling out!
Supply and demand may match at the organization level, hiding skills gaps at the role level, a frequent source of serious project delays
What is the right level to assess alignment? It varies of course, based on task diversity, task duration, and the breadth of staff skills. Looking at individual contributors on a daily basis will always be overkill, but looking at a few dozen, or even 100 distinct roles on a monthly or quarterly basis might be appropriate. A sensitivity analysis that assesses alignment at different levels of detail will help you identify the highest level of aggregation you can get away with.
Drowning in Details
The other reason firms concentrate on top-level views is because using their project management systems becomes cumbersome when viewing, filtering, and pivoting across more than a few dozen roles. Our experience has identified several key activities that must be tractable, at scale, to perform effective resource planning:
- Viewing supply vs. demand at the role-activity level.
- Drilling down to specific projects to understand and (optionally) manually resolve bottlenecks
- Using optimization and scheduling to give priority to critical projects
- Viewing the implications of staffing and project schedule changes as scenarios across the entire book of work
Find and explore the implications of resource bottleneks
If the tools in your toolbox can’t perform these tasks, you might want to consider an open relationship. Solutions based on the Enrich Analytics Platform are designed to scale to hundreds of roles and thousands of projects.
Some Roles are Interchangeable, Others Not So Much
While we’re on the subject of roles, resource pooling is also important. Some roles’ skills overlap to such an extent that they are interchangeable, For ultimate planning flexibility, those roles should be bundled into a pool before matching supply with demand. Without the ability to pool roles into bundles, the staffing plan is missing a critical dose of realism.
For example, a company may have four staff classes that all perform biostatistical analyses. The distinctions may be important for human resources, but the staff are all fully qualified to work on a specific set of tasks. These employees can be pooled into a single staff class for the purposes of the resource planning exercise.
Mapping and role pooling should be point-and-click operations
A Plan Based in Reality
And speaking of realism…we’ve seen organizations forecast staff utilization rates as high as 150% of full-time, even though time-on-task for non-factory employees usually tops out at 80% and averages closer to 60% in R&D departments. This is one instance where extreme optimism is not productive. Rather, using very high utilization rates in the resource plan disconnects the plan from reality and encourages gaming, where staff will pad their hours to come closer to plan, even though competing pulls on their time will make it impossible to actually work that intensively. The end result will be project delays, shifting schedules and diverging forecasts further from your best-laid plans.
Project Delays Make Planning Perilous
Project delays are one of the most common reasons to revisit the staffing plan. And yet, depending on your industry and department, from 30-90% of projects will be delayed. This reality requires two arrows in your quiver:
- The ability to quickly reassess the plan as specific delays become apparent
- The ability to test the robustness of the plan to project delays using simulation and scenario analysis
The first point above underscores the need to have your supply-demand mapping integrated into your planning tools, enabling rapid assessment of new schedules and staffing plans. The second point motivates the need for more advanced analytics, including Monte Carlo simulation, to represent the contingencies of slipping schedules and ballooning costs.
One outcome of simulations like this is an awareness that looking at supply-demand alignment on a daily or weekly basis might not only be overkill, but also over-modeling; delays in project schedules are so pervasive as to make daily or weekly planning to a single schedule misleading at best.
Hiring plans and their implications are easily saved and compared in the Enrich Analytics Platform
Too Many Options to Explore
One reason that resource planning often falls short is because the number of options for overcoming staffing constraints is so large, making assessment and comparison difficult. Options may include:
- Hiring permanent staff
- Hiring contractors
- Retraining current staff
- Outsourcing projects or activities
- Delaying lower-priority activities
- Paying overtime for longer work days
Management’s options become even more layered when facilities and raw materials constraints are included. What is needed then is an agile means to run out scenarios that explore the implications of all the different possibilities. These scenarios must also be assessed in light of schedule and cost uncertainties, as discussed in the previous section.
The rub for scenario analysis is that there is no one-size-fits-all approach: every firm has slightly different options that must be modeled in a unique way to be realistic. This requires resource planning software that can be rapidly customized with the specific levers and dials that represent each firm’s opportunities.
Medium-Term Staff Planning is a Shot in the Dark
For many firms, project staffing requirements only exist for the next six to nine months. This creates a disconnect, because hiring plans may look out a year or more. What is needed is a way to represent long- and medium-term demand even though specific project demand has not yet been identified in that time frame.
Easily define and incorporate placeholder projects in the medium-and long-term demand plans
The solution is an extension of the scenario analysis just discussed, adding placeholder projects to the demand forecast. These placeholder projects are a stylized representation of the future demand based on the profiles of existing projects.
In the Enrich Analytics Platform, customized dashboards allow the creation and inclusion of multiple placeholder projects into the resource plan. This functionality is an important part of resource planning software, allowing management much-needed visibility into the trade-offs of different staffing options. This is especially critical in industries where there is a long lead-time to hiring qualified staff.
Bridging the Last Mile: People, Processes, and Tools
While we think we’ve created some truly unique and invaluable tools for bridging the last mile, we recognize that a true solution requires the right people and processes as well. For example, staff who can gather timely, accurate information to inform scenario analyses are essential, and processes that encourage accurate reporting of both project requirements and time worked on tasks goes a long way to improving integrity of the analyses.
What solutions have you employed for the challenges we’ve mentioned? Are you enduring other challenges we haven’t mentioned here? I’d love to hear about them. And of course, if you’re interested in talking shop about how the Enrich Analytics Platform could be turned towards your resource planning challenges, feel free to reach out.
*We call this a “last mile” problem, a term borrowed from telecommunications networks to emphasize the importance (and difficulty) of connecting the broader network to each customer’s home or office. Without the last mile of connectivity, the network won’t generate a cent of value.
**O’Leary, M., Mortensen, M., Woolley, A., “MULTIPLE TEAM MEMBERSHIP: A THEORETICAL MODEL OF ITS EFFECTS ON PRODUCTIVITY AND LEARNING FOR INDIVIDUALS AND TEAMS”, Academy of Management Review, 36(3), p.461-478, 2011.
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