Evolving Personnel Strategy Alongside Tech Strategy

What Does It Really Mean to Evolve Your Personnel Strategy Alongside Your Tech Strategy?

I often ask my clients, “What are you doing to ensure your personnel strategy is evolving alongside your technology strategy?” It’s a loaded question, no doubt – one that can take a conversation in a million directions, some productive, some not. But it’s a question that I think is important. While technology-based investments are climbing steadily year over year, are we still ensuring the most critical part of any operation – the people – are being equally invested in?

There are more tools, platforms, and tech roadmaps than ever before. When you layer in innovations like AI and organizational changes, such as product-oriented delivery shifts (or other methodologies), it becomes even more complex. So, in an effort to draw attention back to the workforce side of the aisle, I want to share some thoughts about how we can better align our technology and personnel strategies. To avoid oversimplifying the topic, I’ve categorized personnel strategy into three foundational buckets.

There will be temptation for leaders across several technology domains and departments to do more. The aforementioned tools and technologies are undoubtedly driving operational efficiencies, and leaders may feel a bandwidth or a newfound desire to scratch a creative itch. However, before acting on those ideas, it’s important to ask: Do the technology-driven functions and outcomes I’m looking to develop align with our business drivers and what we do?

Many organizations in practices like healthcare, retail, life sciences, and pharma are seeking to “reinvent themselves as technology companies.” It’s not in my nature to try and stifle innovation, but that level of change typically requires a substantial lift when it comes to evolving personnel strategy. So, when evaluating your department’s strengths and domains and determining how much change you can handle, it’s crucial to think about what we do well.

I’ll give an example – a traditional data engineering team. Their role involves data ingestion and integration, managing data, and addressing analytics and dashboarding requests from the business. These teams likely operate as a shared service, supporting multiple lines of business while staying focused on what they do best – data ingestion, management, and analytics.

In this setting, data engineering resources are inherently reactive. That is not necessarily a bad thing, in fact, they’re typically fantastic at what they do. They’re the resources who can build what executive leadership wants to see, and many companies operate this way. The strength of this team is the ability to respond to requests and, when possible, innovate. We see this in operationally driven activities like storage and management, building data pipelines for operational dashboards, and scaling data infrastructure. This is the department's clearly defined strength.

• The data team will build this “thing” and return it to the business stakeholder. Upon handoff, they will now go on with their next ask (perhaps entirely unrelated).

Now, let’s consider the same data engineering team after transitioning to a Product-Oriented Delivery methodology. Let’s also assume there’s been a recent introduction of a tool like Aible (Tableau extension), which brings business users closer to the traditional data team functions.

A team that used to operate as a shared service while supporting the enterprise is now reorganized to align with specific products or lines of business. With this shift comes an inherent push to drive innovation from the technical contributor level.

Here’s where and why the personnel strategy must be addressed. Let’s revisit the same scenario but with a different response and approach.

• The data team, ideally having a deeper understanding of member health records due to the methodology-driven specialization, will evaluate the request and begin thinking proactively.
• The way in which the “thing” is built will be repeatable. This is no longer a one-off request. If we’re showing this data for the Southeast Region, we may as well make this “thing” something that can be easily replicated, as we’re assuming our business stakeholders may have similar interest in the member data for the Northeast, Midwest, and West Coast regions.
• Upon addressing the immediate request, the team may also consider adding data points that create a more holistic view of the member. If we’re pulling the data points for the initial request, let’s allow the executives to also view things like medication adherence, predisposition to chronic illness, and a deeper layer of geographic specificity to understand care gaps in rural areas.

Of course, the second response to the request is ideal. But it’s clear how drastically the expectations and capabilities of the data team members have changed. The technological investments and methodological shifts that have been implemented encourage this type of response, but the difference between this becoming a reality or not lies in the hands of the people.

Some Data Engineering resources from the previous model are willing and able to tackle the scenario in both ways, but that likely won’t be the case for everyone. If we’re underthinking the personnel behind the requests, we’ll find our workforce in a place that is uncomfortable and relatively unproductive. There’s no perfect way to manage a transition like this, but the most important thing is that we begin with being intentional about our people strategy.

In keeping a strength a strength, we need to ask ourselves: Are we prepared to weather and tolerate such a dramatic change? Is our data team’s strength driving innovation and thinking proactively about our business challenges, and then solving them in real-time by integrating solutions into the “things” they’re already providing? Or are they more of a trusted foundation – keeping our data secure and sharing the things we need when we need them?

There’s not a right or wrong answer. What matters is understanding the answer so you can plan to evolve your personnel strategy accordingly, as it’s an extremely difficult thing to do on the fly.

Changes in the technology organization are truly the only constant. In today’s world of AI, ML, LLM, and tools that introduce capabilities that didn’t exist previously, change is only exacerbated. It’s best not to fight it. Much like “Keeping a Strength, a Strength” by defining what we do well, let’s be proactive in generating enthusiasm as it relates to these changes. Where are our gaps in communication?

Minding the Gap is a simple one. Yet, as simple as the message is, it’s often overlooked. If executive-level technology leadership is cagy about the Why behind the investments that are being made or are overly sensitive to political dynamics, the workforce will be far less likely to adapt and adopt those changes.

Messaging change to the execution-layer and individual contributors is critical. By democratizing the decision-making process regarding tools and technology investment, the workforce feels ownership and accountability. Your personnel strategy will naturally evolve alongside your technology environment if you choose to make them part of that evolution.

However, their involvement doesn’t simply happen via a “ride the wave with us” blanket email from the top down. The message needs to be standard and tailored. Line management needs to be empowered to put their own spin on it. It needs to be delivered with empathy, and a balance between willingness to listen to the concerns of individual contributors and a tone of certainty: “We’re headed in this direction, and I didn’t want to spring this on you. We still have autonomy to make the change together, in a way that works for everyone, but this is where we’re headed and why.”

This is where it gets especially hard. How can I listen and lead, defer and drive, enforce and empower? Forgive me for overcomplicating the concept of communication is key. But I think it’s important we evaluate specific scenarios and teams – and get honest with our examples. If we don’t, we’re leaving margins for error and, candidly, we’re being lazy.

Minding the gap simply means, keep a pulse on your leaders. Standardize the message by identifying key components while empowering your line management layer to put their own spin on delivery and giving them the freedom, space, and time to do so. Coaching your coaches can feel iterative in the moment but often creates a downstream effect that streamlines operations and heightens visibility.

Where are your communication gaps?

The ever-present dilemma. Tossing out all the volatility of an ever-changing technology landscape, this is pure fundamentals when it comes to personnel strategy.

There are the classic body of work categorizations that we think about with offshore vs. onshore and in-house vs. outsourced (impact/visibility, desire to innovate, legacy status, static vs. fluctuating, financial evaluation in the aggregate). While those criteria help in deciding what body of work should live where, they don’t necessarily apply to an internally driven personnel strategy.

As an avid baseball fan, my mind immediately goes to the immense value that a healthy farm system provides. Fantastic scouting and player development (and deep pockets, à la Dodgers) improve the big-league ball club’s performance in the immediate, and future-proof the organization for years to come.

In this case, however; I feel like a more apt sports analogy lives in the NFL. The two thought processes are typically Draft & Develop or Acquire in Free Agency. Here’s a simple table to highlight transferrable components to each strategy that apply in enterprise technology leadership and the NFL.

**Please note, I’m an avid fan and not a GM.

The best solution is a healthy mix of both. You draft and develop players and assimilate while simultaneously building and strengthening your culture. This is also something that doesn’t happen in a vacuum. Picking up a key free agent in a year where the playoffs or a championship are achievable right before the deadline may just be the thing that takes you over the top (Johnny Cueto, Kansas City Royals 2015).

Here's a roster percentage of drafted or undrafted free agent “homegrown” talent from the last 10 Super Bowl winning teams:

In evaluating these team constructions, the winning group is almost always 50% or above “homegrown”. Now, I’m well aware of the fallacies that exist with this comparison. DevSecOps, Data Engineering, AI, ML, App Dev teams are not Offensive Linemen, Wide Receivers, Running Backs, and Quarterbacks. But why do they have to be so different? Foundationally, we’re building a multi-faceted group with varying specialties that performs at a high-level, works together, and pivots when encountering a variety of opponents and obstacles that could prevent them from reaching their ultimate goal.

The primary advantage in the Draft & Develop or Build > Buy methodology is price point. What those Super Bowl champion rosters also reveal is that those aren’t just affordable players, they’re winning players.

Summary:

We must ask ourselves: Are we putting band-aids over bullet holes by relying on overpriced free agents? Are we effectively investing in our people pipeline, and do we have an intentional, thoughtful, technology-environment strategy that allows us to achieve the ultimate goal?

Technology leaders are facing ambiguous, complex challenges when it comes to their technology and personnel strategy. By addressing both simultaneously, we foster innovation, reinforce our company culture, and make our company a place people want to be.