Bridging from Digital Topics to People Implications
Michael and I recently had the joy of facilitating a change community of practice discussion on HR and Digitalization. We talked with dozens of human resources professionals, lean six sigma practitioners, and change managers about how to connect the dots between digital initiatives and people implications.
We weren’t talking digitalization just for the fun of it. The group’s overarching goal is to make it simple for business leaders to succeed in technology projects, and our topic included a straightforward framework for participants to use in discussions with business and technology leaders around digital-centric projects.
We began with an assertion that won’t surprise frequent readers of this blog or business transformation practitioners:
Every digital enablement decision has human capital implications.
People implications of digitalization come in many forms. To begin, consider:
Are we making processes fit technology, or technology fit processes?
Will team members need to learn new skills, as well as a new technology?
How can our spans of control shift with a new digital technology?
How will we need and upskill to retool human capital?
How will this impact our customers and/or employees? How do we expect them to respond?
With the start of a sense for how technology will impact people, it is helpful for us to turn to human resources, people operations, and change leaders. They have critical knowledge to share around:
Navigating change
Retooling employees
Identifying and building capabilities and skills
Making the most of organizational structure and supports
Anticipating and managing resistance to change
But how do we connect the dots between a proposed digital initiative and people implications?
The FlexPoint team has compiled technology questions and corresponding people implications for four common digitalization areas:
System / Platform Modernization
AI & Automation
System Rationalization
Reporting & Analytics
These are far from exhaustive, but they can get you started in bridging from digital topics to their people implications.
System / Platform Modernization
Technology Questions
How can we replace this legacy mainframe system with a modern cloud-based technology?
Which new system should we implement?
What is our Buy vs. Build (and standard vs. custom) approach?
People Implications
Will resources supporting the legacy tool retire? When? Will we have to plan reduction(s) in force?
What new skills and expertise do we need? Do we need to hire? Train? Upskill?
If we’re buying off-the-shelf software, how will our business processes change? Are we equipping our users for that?
Real-World Example
In coaching our clients through platform modernization efforts, we recommend including business stakeholders through the entire project, not just at the beginning (tool selection) and the end (user acceptance testing). One reason we feel so strongly about this is that we’ve seen systems selected because they can meet functional and technical requirements, and then the technology team configured the software prioritizing technical flow over business processes.
This tends to happen incrementally, and many process updates to take advantage of strong out-of-the-box flows are worth the adjustment, but we’ve seen the project team take the new solution too far in one direction, only to have frustration when they brought it back to end users for testing.
AI & Automation
Technology Questions
What low-value tasks and processes can we automate?
What tools and technologies will we use (RPA, AI, etc.)?
Where can we build AI models to predict events and behavior?
People Implications
Who is doing the tasks in question today? Do their jobs change or go away?
How do we equip our team members to “collaborate” with the automation to ensure a seamless experience?
Do we have the right in-house technical talent to build and maintain AI models? Do we have the right business SMEs involved?
Real-World Example
The community of practice participants had several examples of AI and automation advancements with technology and people implications. One example we discussed was the growing need for well-structured knowledge management with greater reliance on chatbots. They previously had reference materials stored in a variety of formats and found that it helped produce better chatbot results for people with expertise in the subject area to translate existing materials into a standard template.
That is, in order to free up individuals’ time via effective generative AI use, they needed to invest meaningful time upfront.
System Rationalization
Technology Questions
Which systems can we consolidate, rationalize, or deprecate?
Which system will be our “standard” for the future?
What is the timeline for technical implementation?
People Implications
Who is doing the tasks in question today? Do their jobs change or go away?
How do we equip our team members to “collaborate” with the automation to ensure a seamless experience?
Do we have the right in-house technical talent to build and maintain AI models? Do we have the right business SMEs involved?
Real-World Example
The example we discussed in the community of practice meeting seemed innocuous from a technology perspective, but there were a ton of people implications just under the surface!
An organization was acquired, and one of the integration items was to move from Slack (the legacy chat platform) to Microsoft Teams (the collaboration tool of the acquiring team). The integrating team had created hundreds of custom emojis in Slack and had built strong bonds in communicating through the tool. At that point, Teams didn’t yet have custom emojis, so the acquired team felt a cultural loss in shifting to the enterprise platform.
Michael made the point that custom emojis doesn’t often show up in a tool selection checklist, but the shift from Slack to Teams had real cultural considerations to work through.
Reporting & Analytics
Technology Questions
What is our plan to standardize onto a single reporting tool?
What are the most important reports to build for Go-Live?
Is our data high quality and trusted?
People Implications
Who gets what reports today? How do they actually use these? Are reports driving the actions we expect?
Even if we build the right reports, do users know how to use the new reporting tool or platform?
Do we have clear data ownership and governance standards? Do individuals know what their responsibility for data is?
Real-World Example
New reports, dashboards, and analytics offerings can be so exciting! And while the team is dreaming up, designing, and building these upgrades, we typically incorporate meaningful improvements from the status quo based on information being combined or presented better than it is today. But don’t forget that those who rely on the reports will want to test that they provide at least the same insights as today’s versions to, and just being told “trust us” isn’t going to cut it.
So, be prepared to provide a way for report users to tie out each data element that they rely on. This can be accomplished in an interim testing step — “we’re building the new reports with these foundational components and want you to test them along the way.” Or we can include extra data elements at least temporarily in the new report for users to compare with their previous version and get comfortable.
Whichever path you go down, expect to earn the trust of those who use the new reports or dashboards, rather than expecting them to trust that you’ve fully tested the new offering. After all, they are doing important work based on the information provided, so they’ll want to minimize disruptions in adopting a new approach.
When we prioritize the people implications of digitalization, we increase the impact and effectiveness of technology efforts. We hope you’ll include some of these questions in planning your next technology effort!
