Beyond billable hours

The billable hour isn't really the problem

There is a legitimate criticism of the traditional consulting model: too often, the mechanics of an engagement become disconnected from the reason the engagement exists in the first place.

A company does not invest in a new ERP system simply because it wants an ERP system. It wants better visibility into its business, more reliable operations, faster processes, stronger controls, or a platform capable of supporting what comes next. It does not automate accounts payable because it wants an automation project. It wants to reduce manual effort, shorten processing time, improve accuracy, and allow people to spend their time on more valuable work.

Yet consulting engagements are frequently defined and managed around something else entirely: hours, resources, project phases, workshops, requirements documents, configurations, and deliverables. Those things matter because they are how work gets done, but they are not why the work is being done. Confusing the two makes it possible for an engagement to be successfully delivered according to its project plan without necessarily producing the business improvement that justified the investment.

It is tempting to conclude that time-and-materials consulting itself is therefore the problem. There is some truth to the criticism. When revenue is directly proportional to hours worked, efficiency can create an uncomfortable economic tension. But different kinds of consulting also involve different kinds of uncertainty. An organization troubleshooting a complex production problem may not know what the solution requires until the problem is understood. A transformation program may evolve as business requirements become clearer. In situations like these, time and materials can be an entirely sensible commercial model.

In other situations, it makes much less sense. If an automation has a clearly defined scope and measurable economic value, pricing it solely according to the hours required to build it can actually penalize expertise. The better a consultant becomes at solving the problem, the less the work is theoretically worth.

The issue is not whether consultants charge by the hour. It is whether the commercial model reflects the nature and value of the problem being solved.

Start with what should be different

Before deciding how an engagement should be staffed, scoped, or priced, we believe there is a more fundamental question to answer: What should be different when this work is finished?

Consider a company that wants to automate a manual pricing process. One way to define the project is around its outputs: build an integration, create an automated workflow, configure the application, test it, and deploy it. All of those may be necessary, but none explains why the company should make the investment.

Another approach begins with the business condition the company is trying to change. Perhaps employees spend ten hours each week collecting and entering pricing data. Perhaps pricing errors create downstream corrections. Perhaps updated market prices take two days to reach the systems where decisions are made. Once those facts are understood, the objective can be expressed differently: reduce manual processing, eliminate duplicate entry, improve accuracy, and make validated information available faster.

The integration, workflow, testing, and deployment are still necessary. But they are now means to an end rather than the definition of success. That distinction affects decisions throughout the engagement. A feature that adds complexity without advancing the desired outcome becomes harder to justify. A simpler approach that produces the same result becomes more attractive. The project begins to optimize around the client's problem rather than the volume of work available to perform.

Measure the result, but recognize shared accountability

Taking outcomes seriously also means taking measurement seriously. If the objective is to reduce invoice-processing effort by 50%, both parties need some understanding of what processing effort looks like today, how improvement will be measured, and which data will be used to determine whether it occurred.

That does not mean every engagement needs an elaborate measurement regime. The rigor should be proportionate to the investment and the outcome. But establishing a baseline before significant work begins is considerably more useful than attempting to reconstruct one after implementation.

There is another important complication: consultants rarely control the entire result. A consulting team may design the right architecture and build the right solution, while the client still controls decision speed, data quality, organizational change, user adoption, policy enforcement, and executive sponsorship. Other vendors and technology platforms may control additional pieces.

This is why we are cautious about simplistic promises to "guarantee" business outcomes. For the right problem, putting consulting fees at risk can create powerful alignment. For others, the result depends on enough variables outside the consultant's control that the contractual machinery required to assign responsibility can become more complicated than the problem it is intended to solve.

We prefer the broader principle of shared accountability: understand what the consulting team controls, identify what the client controls, make the important dependencies visible, and agree on how progress will be evaluated.

The commercial model should follow the problem

There is no single commercial structure that is right for every consulting engagement.

Time and materials works well when the work is exploratory, requirements are evolving, or the client needs flexible access to expertise. Fixed-fee engagements make sense when the scope is sufficiently understood that the consulting firm can reasonably assume delivery risk. Milestone-based structures can work when an engagement naturally progresses through objectively verifiable states. Value-based pricing becomes attractive when the economic value of solving the problem can be estimated more reliably than the effort required to solve it. Outcome-aligned structures, where some portion of compensation depends on measurable business results, can be powerful when the result is measurable and the consulting team has enough influence over it to accept meaningful performance risk.

The sophistication is not in choosing the most fashionable model. It is in knowing which model fits which problem.

That distinction becomes particularly important when clients hire specialized, senior teams. Imagine two consulting firms solving the same business problem. One assigns a large team and requires 2,000 hours. The other uses a smaller group of experienced people, recognizes the pattern quickly, avoids unnecessary work, and solves the same problem in 600 hours. Under a purely effort-based interpretation of value, the second firm should earn substantially less.

That is a strange economic conclusion. Expertise should create leverage. The accumulated experience that allows a team to identify the right architecture sooner, avoid a failed approach, or eliminate unnecessary complexity is part of what the client is buying.

Small, senior teams in an AI-enabled model

This principle influenced how we built Velocity Advisors. We deliberately built around small, senior teams rather than the traditional consulting pyramid in which large numbers of junior resources support a much smaller layer of senior leadership. We wanted the people helping shape the strategy and architecture to remain directly involved as those decisions became working systems.

AI makes that model more powerful, not less. When experienced people have better tools, the objective should not be to recreate the labor pyramid with technology. It should be to accomplish more with fewer handoffs, less organizational overhead, and more direct involvement from the people accountable for the solution.

The opportunity is to create an economic model in which productivity benefits both sides. The client gets to the result faster and with less organizational burden, while the consulting firm is rewarded for expertise and efficiency rather than for maximizing labor consumption.

That is also why we do not view outcome alignment as synonymous with outcome-based pricing. The pricing mechanism is only one part of the equation. The more fundamental principle is to design the engagement backward from the value it is intended to create.

Designing backward from value

A well-structured engagement should be able to answer a few questions clearly.

• What business problem are we solving?
• What is true today?
• What should be different afterward?
• How will we know?
• What does the consulting team control, and what does the client control?
• What assumptions could materially change the result?

Only after those questions are understood should the parties decide which commercial structure best distributes the risks and rewards between them. Sometimes the answer will still be time and materials. Sometimes it will be a fixed fee or milestone structure. In the right circumstances, it may involve shared savings or compensation tied directly to an agreed result.

It is notable to see some of the world's largest consulting firms moving further in this direction. We welcome the evolution. But we think the conversation becomes unnecessarily narrow when it is framed simply as the death of the billable hour.

The more important change is in how consulting firms think about what they sell. Consulting should not begin by asking how many people can be put on a project or how many hours a body of work can support. It should begin with the client's problem, the value of solving it, and the most effective way to get from one state to the other.

That principle has been part of Velocity from the beginning: small senior teams, direct involvement from strategy through execution, technology selected in service of the business problem rather than the other way around, and commercial structures appropriate to the work rather than imposed by convention.

The hours, architecture, implementation, and deliverables all matter. They are necessary ingredients of good consulting. But ultimately, they are inputs. The reason for the engagement is what changes afterward.