Why are the right skills never available when you need them?

In our contemporary business climate, organizations increasingly need to deal with a volatile and changing market. One need only mention VUCA to an executive to start a conversation about today’s business challenges.

As I spent several years working on this challenge supporting my organization, one problem continued to hound me: how to have the right skills available to match our market’s volatility, in short: high skill liquidity. For much of the time it felt like I was experiencing an endless loop: organize for optimal skills, experience market change, organize for optimal skills, repeat.

But how can we make skills more liquid for our organization? The ability to tap into the necessary skills without long delays and expensive transaction costs. But humans are, for better or for worse, fairly complex particularly as they apply their skills in knowledge work and can’t be managed as if they were commodities.

This problem can’t be taken lightly; not having the skill capabilities available to execute can create significant bottlenecks, introducing delays in your market offerings and ultimately showing up as gaps in your competitiveness.

Much has been attempted to address this volatility, particularly adapting concepts from organizational approaches such as Lean, Agile methods, Kanban and TPS to name a few. Interestingly some of these approaches have suggested their own particular solution; such as “Cross Functional Teams” popularized by Scrum practitioners. In examining and leveraging various approaches, I began to observe that many of these methods have a lot to offer, and are not contradictory — particularly if you reframe them as one of many compounding approaches across a maturity continuum.

Introducing the Skill Liquidity Maturity Model (SLiMM v0.5)

Figure 1 — The Skill Liquidity Maturity Model v0.5

In introducing the Skill Liquidity Maturity Model, I chose to use a seven-level scale to allow for easy alignment to existing models, including the recently launched Kanban Maturity Model (KMM). The KMM in particular already being fairly robust in aligning or incorporating from multiple areas including Lean/TPS, Real World Risk, CMMI and Mission Command. As part of that alignment the first Skill Liquidity Maturity Level starts at 0 and the 4th and 5th are labeled 3&4 and 5&6 — this is to map appropriately to KMM’s existing maturity levels.

Skill liquidity is not the only aspect of organizational maturity. My intent is that this is useful to you, by complementing any other models you may already be using.

The maturity levels are intended as building blocks, higher levels leveraging those beneath them as underpinnings for the more mature practice.

Maturity Level 0 — Skills Specialization

Figure 2 — Each individual has a specific skill. Denoted by shape and colour.

At the lowest level of maturity, we start with skill specialization, the practice of staffing your organization with people with the required skills necessary to offer your current services/products. It’s a natural place to begin, and just about every company starts here, and most remain. You can see evidence of it in many company’s hiring process where the primary focus is on the required skills of a candidate for a particular role.


This approach offers several advantages, the hiring process can be relatively simple — assuming the skill you are looking for are readily obtainable. Formal job descriptions can be used to define the expectations and limits of a particular role.

From a personal-employee standpoint it offers the opportunity for long term development of a particular niche set of skills — to the point of craftsmanship.

Limitations & Challenges

The long-term challenge with this approach is in the unevenness of the market demands on your business, both in volume and service type. Where once an organization required a certain number of specialists in an area — they may find themselves quickly over or under allocated.

The over-allocation problem typically manifests itself as bottlenecks within an organization, impeding the delivery to your customers. The under-allocation can be seen as the over investment in non-competitive categories — over serving a particular market.

Skill specialization mindsets tend to propagate to how organizations as a whole get organized. Teams with specializations, departments, and divisions — in short, your typical Matrix Organization. There is nothing intrinsically natural about having an IT, Finance, or HR department; they are simply constructs of specialization-based organizational practices that we’ve gotten used to as a norm. These constructs provide deep expertise, but do introduce bottlenecks.

Maturity Level 1 — Multi-Skilled Individuals

Figure 3 — T-Shaped skilled individuals have primary specialties and secondary skills. The large shape denotes the specialty, the smaller the additional skills.

An attempt to address the liquidity limits of skill specialization gave rise to the concept of “T-Shaped” individuals, first popularized by Tim Brown (IDEO) and supported by multiple Agile frameworks. The concept of the T referring to the acceptance of individual specialties along with the development of secondary adjacent skills. In software development, the example would be the front-end software developer who is also able to make changes to the database.


The advantages with this approach is to reduce the frequency of requests from other specialties. Continuing with the Software Developer example, an individual when requiring relatively simple, and possibly frequent, changes to the database does not need to wait for a Database specialist; this reduces a potential source of bottleneck in the organization.

For people whose passion is to develop skills in multiple areas, working in an organization with this approach can be both satisfying and provide for multiple paths for career development.

Limitations & Challenges

The hiring process does get more complicated, in addition to looking for the primary skills sought out, the ability and interest to develop adjacent skills need to be determined. In some cases, highly skilled specialists may not be interested in taking part in a structure looking to impose this approach to everyone. This lack of interest may be rooted in the identities of highly skilled craftsman and can cause cultural challenges if forced. To quote a famous fictional doctor, “I’m a doctor, not a coal miner.” Organizations that work well at this maturity level have figured out to not impose this on all employees and allow for pockets of individual specialization.

Companies at this level of maturity continue to organize around specialization. As in ML0, when observing their organizational structure you will find discrete departments providing specific functions: Marketing, IT, Accounting, etc.

Human limits to the depth and amount of auxiliary skills one can develop introduce either skill-development delays or continued requests for access for more specialists.

At this level of maturity, common sources of adjacent delays to individuals are improved, but team and organization bottlenecks persist.

Maturity Level 2 — Cross Functional Teams

Figure 4 — Cross functional teams inherit the overall skills provided by those individuals within them. Boxes are solid around the team denoting clear team boundaries.

Popularized by methods such as Scrum, the cross functional team is the mix of (preferably T-shaped) people with different skills into a single team. A common example is a software development team that used to hand completed work to a testing team — in the cross-functional configuration a single team would have the capability to both develop and test software.


Cross functionality looks to reduce the frequency in which a team needs to leverage help from outside the team; perhaps from another team, specialist or shared service. Interactions between teams are a common source of delay and so cross functionality reduces the frequency in which this occurs and to reduce delays.

Figure 5 — Cross-Functional eliminate hand-offs that would have been experienced by specialist teams.

The variety of skills also allows for a team to produce more combinations of possible work. It provides organization’s with increased flexibility with what work they can offer to the market.

In the figure below, you can see this demonstrated.

Figure 6 — Given the ability to produce one thing per team at a time, in this example 3 cross-functional teams can produce 10 different possible combinations of outputs. The specialist teams can only produce one possible combination.

Limitations & Challenges

As companies work on both an increased variety and volume of work, the ability for single cross functional teams to provide the capacity and variety of skills needed quickly reach their limit.

At some point it is not economically cost effective to develop every possible skill into a single team. For example, a team may need to redesign the UX of their application every 2–3 years; for that low frequency it may not make much sense for a team to invest heavily on UX expertise beyond what is required for regular upkeep.

Team sizes all provide for practical limits to the amount of skills a team can possess. Good team sizes tend to have ranges between 4 to 10 people (“1 to 2 pizza team”), the attempt to sufficiently provide for all the skills needed for complex deliveries would significantly expand on that number.

Cross-functional teams can also allow for the flow of low value work when their skills do not match business needs. A common pattern seen is one where a team’s top priority, limited by their skills, is not the optimal work for the organization. If allowed to persist over a period of time, team tribalism and self-organization patterns can lead to teams developing identities around their skill mix in contrast to the needs of the organization’s customers.