Michael Bertha
Contributor

An archetype-based approach to driving your global workforce transformation

Opinion
Mar 11, 20246 mins
IT LeadershipIT Strategy

In transforming your IT workforce, modeling its to-be composition is a necessary and smart first step, but it represents only the tip of the iceberg. Here’s how to pressure-test your model against the realities of execution.

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This article was co-authored by Michael Bertha, Partner, Metis Strategy, and Ishan Prakash, Manager, Metis Strategy

In today’s ever-expanding digital landscape, in which many IT teams operate across geographies, it’s no secret that your ability to leverage technology to its fullest depends crucially on your workforce composition: on how your resources are allocated across various sourcing models, namely, FTEs, onshore, nearshore and offshore. As technology becomes ever more important to strategy, IT leaders are reconsidering their workforce compositions. Where they once optimized predominantly for cost, they’re now weighing that one variable more carefully against many others, including productivity, digital maturity, and the development of longstanding capabilities. 

And though modeling the composition of a to-be workforce is a necessary and smart first step, it represents only the tip of the iceberg. In other words, it’s unrealistic to redeploy a role as part of a different sourcing model and expect instant productivity gains. Countless variables must be considered: skillset alignment and maturity, time zone differences, and ways of working (both within a team and across the organization), and so on.

Acknowledging these challenges and complexities, how can one pressure-test their spreadsheet exercise against the realities of execution? Drawing from our collaborations with several Fortune 500 clients on this topic, we suggest an archetype-based approach, one that, when executed well, will allow you to charge ahead with implementing your to-be workforce composition, and with the confidence that it reflects the needs of your organization.

Step 1: Assess the demand profile

By shifting the composition of your workforce, you are bound to affect certain functions, capabilities, or products. Begin by understanding those entities’ remit and ways of working. Are they developing novel products and services? Configuring a package solution? What key technologies are they using? What skills will enable operations in the new model? Are they working in agile? If so, what flavor do they employ?

As an example, consider the case of a global retail client. In assessing the demand profile of the team that oversees their fulfillment capability, the client examined their inventory management solution, a niche one, and determined that, even though the company might benefit by bringing the solution’s support team nearshore, the right skills would be hard to find in the short run.

Cataloging the answers to these questions provides a fact base that allows you to understand what capabilities, roles, and skills will be needed to support demand. And perhaps equally important, it allows you to understand which of those capabilities are fungible across sourcing models, and which are, at least in the short run, tied to specific locations or vendors.

Step 2: Create the master set of archetypes

After constructing a demand profile for each function, look across those profiles. Reconcile and rationalize them. And make sure the various types of demand will be supported by creating a master set of archetypes.

What’s an archetype? In this context, archetypes encompass the roles, responsibilities, and geographies that constitute a specific capability and that are required to support a certain type of demand.

As an example, consider the archetypical teams found at one of our global retail clients. For one, they have an infrastructure delivery team archetype, which consists of a nearshore engineering delivery manager, a scrum team, and both a nearshore and offshore delivery team (i.e., developers), the latter supplementing the former with overnight or follow-the-sun support. They also have single or multi-capability delivery teams that work on, among other things, innovation and product development, and operations and maintenance. As you can imagine, the archetype after which these teams are modeled varies based on the demand profiles they are constructed to satisfy. While every organization is different, we often challenge our clients to limit themselves to six archetypes. 

By undertaking this exercise, you not only confirm that your teams are structured such that they can both support demand and satisfy the objectives of the workforce shift; you create a vehicle for scale and standardization in what is likely to be a multi-vendor, multi-geography workforce. 

Step 3: Apply the archetypes and perform a gap analysis

Having established a master set of archetypes, it’s crucial to apply them to each function’s to-be workforce composition. Doing so will reveal discrepancies between those archetypes needed to satisfy demand and those targeted for the to-be workforce compositions, which may have been painted with broad strokes in a top-down exercise that gave little consideration to execution. 

By applying the archetypes to your to-be model, you will quickly see where your current workforce easily ports into the new model, and where there are gaps that must be closed through some combination of reskilling, recruiting, and partner sourcing. The time it takes to execute these tactics will inform the speed and sequencing of implementation.

Here you can also take stock of the various ways of working practiced by the different capabilities or functions. If those capabilities and functions work similarly then perhaps it will suffice, as responsibilities change in the new model, to simply recalibrate planning and execution processes. If they work quite differently, however, then a major change will likely complicate both their work and the effort to shift the workforce composition. The discrepancy may indeed merit a broader reset as you move toward the to-be model. It is also at this point that more attention tends to be given to an organization’s horizontal capabilities. One such capability that often surfaces is Knowledge Management: how do we ensure that in changing or relocating a resource, we don’t lose critical institutional knowledge? 

Results: a workforce transformation that is purpose-built for the realities of execution

By the end of this exercise, you will have effectively pressure-tested your to-be model. You will have uncovered a clear set of gaps that, when accounted for in your roadmap, will help you avoid surprises as you move towards the to-be workforce model. You will also have created a set of archetypes that transcend the seams of your workforce ecosystem and bring harmony and scale to your multi-vendor, multi-geography workforce.

If your organization is anything like those of our clients,’ you will have realized that a shift in global workforce composition, what may initially feel like a lift and shift of resources, is akin to engineering a skyscraper: structural integrity, precision, and attention to detail are paramount to ensuring that the building can withstand any pressures and function according to the needs of its occupiers and stakeholders. 

Michael Bertha
Contributor

Michael Bertha is a Partner at Metis Strategy, a strategy and management consulting firm specializing in the intersection of business strategy and technology. Michael is the Head of the firm's Central Office, where he advises Fortune 500 CIOs and Digital executives on the role that technology plays in differentiating the customer experience, developing new products & services, unlocking new business models, and improving organizational operations. Prior to joining Metis Strategy, Michael spent 9 years in the IT Strategy practice at Deloitte Consulting, where he focused on working with senior leadership teams across several industries on strategic, IT-enabled business transformations. Michael has an MBA from Cornell University, and a master’s degree in the Management of IT from the University of Virginia.

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