Most organisations vastly underestimate how wasteful they are with their resources. We need to get much better at thinking systemically and acting systematically in the planning and performance of our work. To aspire to achieve lofty goals, we must lift our ability to properly measure and deeply understand the immutable laws of the supply of, and demand for, the human, material, information and financial resources that power our intentions.


This is Part 1 of a series. Read the other parts here:

Part 1: On being resourceful: the problem
Part 2: A quantum leap in resourcefulness

[Listen to audio version, read by David Hodes]

In my article on two-tier scheduling, I wrote about the demand side of the supply and demand equation. The schedule, based on the scope, determines the demand for resources; the challenge is then to find the Goldilocks value of the supply side. Here, I’d like to highlight the supply side. Overloading on resources not only costs money, it also creates complexity and confusion. How do we know what resources you have available to do the work demanded by your plans?

Let’s start with what I mean by resources in the first place. Any resource taxonomy must begin with identifying the human, material, information and financial resources—by type, in time and space—able to do the the work of turning intention into reality. Human resources can be broken down into the specific capabilities required in a given work environment. Material resources include parts, whether manufactured or bought, and equipment, whether owned or hired. Treating information as a class of resource is not so common. But when you properly manage all the terabytes of data you produce—and ask the right questions of this repository—you uncover a resource of strategic competitive advantage. And of course, money makes the world go round.

“All systems have constraints governing
the rate at which value is created”

At its root, the Theory of Constraints (TOC) is a means of understanding, at an operational level, the laws of supply and demand. Through the genius of its inventor, the late Eli Goldratt, we have come to better understand the fundamental axiom that all systems have constraints governing the rate at which value is created. In the language of the laws of supply and demand, if I have demand articulated by a project or production schedule and supply articulated by my resource availability, then I should be able to compute where my bottleneck is.

The domain of expertise where these calculations are done is called finite scheduling or, in the language of capability maturity models, quantitative work management. Whilst it sounds simple in theory, moving to a capability that allows the organisation to quantitatively express supply and demand is anything but. Why?

A taxonomy of capability
Let’s look at the three key stakeholders involved in resource management: Finance, HR and Operations, whether projects or production. Finance is interested in two fundamentals: how much are we going to spend and when are we going to spend it? Typically, they will control outgoings through purchase orders and are only really interested in matching the claim from the vendor with what has been agreed to contractually. HR is primarily concerned with recruitment, on-boarding and off-boarding, and ensuring that qualifications are valid for the scopes of work being undertaken.

Within Operations, the project teams need to know to a much finer level of resolution how many people of each capability are available on any given day, what they are capable of doing and how the work they have in front of them is going to be effectively supervised. Think about that for a moment. Firstly, project managers have to have a resource taxonomy which clearly defines, in terms which database queries can process, what discipline the person comes from, what skill type is required, with what level of specialisation, where they are in the hierarchy, what organisation they belong to, and where they are going to do the work.

Once you’ve decided on the taxonomy for the master data, it has to be applied to both the schedule side of the equation, such that it can articulate demand, and to the budgeted positions to articulate supply. Let’s suppose you’ve managed to sort out this non-trivial exercise, and are able to control the propensity of one set of people to call someone a ‘mechanical engineer’ and another to go for ‘engineer: mechanical’. What then? Well, when are they going to be available to do work? What rates will apply—for standard time, as well as overtime? What are their rosters and when will they have time off? What if they want to take a holiday or have reason to be away from the project because of some form of business travel? And how do you know they’re even there? Because you’re being billed for it?

On most of the assignments I’ve worked on there is an additional complicating factor: not all resources required for a given project come from a single organisation. Indeed, there are often several organisations, with overlapping and complementary skillsets. How do these all get reconciled to form a view of who is legitimately on board? Who is actually available to do the work? One company uses SAP, another PeopleSoft and yet another Oracle for their HR records.

None of these systems talks to each other and, besides, how they represent their resources in those ERP systems is of no use to a project manager trying to match them with the resource types used in their own schedules. Maybe they have a learning management system (LMS) which can identify people’s qualifications. But again, more often than not, these are set up to meet regulatory requirements and the structure of the data is not fit for the purpose of articulating aggregate supply by type, in buckets of time, in specific locations. And of course it’s very difficult in most scheduling tools to articulate a clear management hierarchy with managers, supervisors and team members all accounted for down to the level of the finite element of work.

So, all the information that’s fit to process ends up in the mother of all spreadsheets, with little to no control of data integrity and significant lag between what the records are showing and what’s actually happening in the field. Somewhere in all of this, a pitiful data clerk tries to keep up with the vendor claims, looks out for double-dipping and goes to extraordinary efforts to reconcile the plethora of rates and allowances agreed to in the contract.

Avoiding the thieves of value
There are three material consequences to not getting the resource mix right—that is, having too many or too few of any given resource type:

1. You burn through more money than you need to
2. You clog or starve the flow of work, and hence limit value
3. You delay the achievement and reduce the magnitude of profit potential

Make no mistake, the consequence of not taking a disciplined approach to managing resources mindfully can be enormous. On one assignment I led, we were onto the fourth release and ninth Go Live of a multi-year implementation of a global ERP system. We thought we had our act together and that our resource and schedule management was best of breed. Indeed, in a previous release, an independent peer review gave us only a 3% chance of hitting our Go Live date—yet we got it done on time and well below budget.

However, when we plotted the load versus capacity for this fourth release, we looked at the graph (recreated below) and scratched our heads: with the tight discipline we applied to the planning and performing of work, how could we achieve a schedule density of only 34%? That is, for that class of resource who had no other work to perform other than what was in the Gantt chart, we were paying them for twice as much time as the schedule said we needed them—and that itself was planning to a prudent 80% of nameplate capacity. The difference between the 34% and the 80% utilisation amounted to anywhere between $100m and $200m, depending on how it was calculated.

To this day, I think the insights gained in that exercise are as significant as Taichi Ohno’s revelation that despite the machine-time spent on a part being measured in minutes, the inventory held of that part is often measured in months. How could such waste be tolerated, let alone sustained?

In my next article, we’ll explore the methods and tools required to effectively articulate the supply of resources so they can be measured to meet the demand of the work planned within your enterprise. This is an unglamorous undertaking but pays enormous dividends not only to your organisation’s productivity and financial health, but to all those working in the system. People can finally understand the goal and see upcoming tasks in a way that lets them work in flow without burning out.

How do you bring this together to do more with less? Find out in Part Two: A quantum leap in resourcefulness

If you want to learn more about how TOC can help you focus where it really counts, why not schedule a video call.

This is Part 1 of a series. Read the other parts here:

Part 1: On being resourceful: the problem
Part 2: A quantum leap in resourcefulness

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What’s next?

The change from standard thinking to Theory of Constraints (TOC) is both profound and exhilarating. To make it both fun and memorable, we use a business simulation we call The Right Stuff Workshop.

We’d love to run it with you. To learn more:

• download the brochure (no email required)
• schedule a call

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  [Background photo: ‘Computer code’
  by Markus Spiske on Unsplash]

  “Progress cannot be generated when we are 

  satisfied with existing situations”
  —Taichi Ohno