Hiring People "Not Like You"
How to solve the data-readiness gapAdd bookmark
SSON’s State of the Shared Services and Outsourcing Industry – Global Market Report 2021 points out the “data-readiness gap” as an obstacle to achieving the next stage of value proposition. But what makes up this gap: people, process, or technology?
We have all experienced the vendor “hype-train” around RPA/AI/ML, etc. so it can’t be that the technologies don’t exist. Also, process mapping, mining and management are having their moment as enterprises recognize that business process is the elemental, organizing principle for efficient/effective work. There is indeed a demand/supply imbalance with respect to process leaders and experts, but what is the real bottleneck?
It is finding people with the talent/skills to leverage all the rich data flowing through shared services as transactions are processed. I believe that the solution is to start hiring staff who are “not like you” to capitalize on opportunities to leverage this vast trove of data for analytics, insight, and action to optimize business operations.
Where are these digitally skilled professionals that are needed to fill the gap? To narrow it down, I will tell you where they are not.
People with the skills needed to effect rapid digital transformation will not be found in the same college/university business and accounting programs you have been tapping for years to find interns and new hires for finance and shared services.
Also, don’t look to refugees from IT departments (there are exceptions) who have been indoctrinated in the ITIL framework and consider an attempt of business-side organizations to digitally transform themselves a “wildcat” initiative that should be stamped out, much less supported.
Who then? There are people who occupy a middle ground, between a deep finance/business-centric orientation (e.g., accountants) and an engineering/technical perspective (e.g., developers). Earlier in my career, I heard this group referred to as “Z People” (not to be confused with Generation Z) because they possessed an understanding of business (x-axis) along with a foundation of technical skills (y-axis). I believe that demand for Z People is greater than the naturally occurring supply, so finance and shared services organizations must approach the challenge in a different way.
Instead of hiring for finance skills/experience and hoping for digital aptitude, finance/SSO leaders must send the message to their organizations to target those “not like you” and be willing to teach them the finance process knowledge required.
Hoping is not a viable staffing approach for digital transformation. It is time for hiring managers who are tasked to effect digital transformation to get out of their comfort zone.
The solution is to start hiring staff who are “not like you”
One way that leaders, especially in finance and business-related areas, have achieved their career growth is by being excellent organization builders, surrounding themselves with younger versions of themselves. These teams are made of functional experts in accounting, tax, P&L, balance sheet, cash flow, etc. The bulk of staff have attended the same/similar universities. The course of study was roughly the same: accounting, economics, business law, organizational behavior, etc. Maybe there was an information systems course or two, to educate about enterprise resource planning (ERP) systems with an emphasis on how the general ledger was at the center of all business process activity in an enterprise.
This approach worked well as business operations evolved, advancing on a consistent trajectory of mostly the same, but better, faster, and more efficient work. This approach will not work if rapid, digital transformation is the goal.
Demand for Z People is greater than the naturally occurring supply
I did an internet search for undergraduate university course schedules for accounting/business administration (below left) and data analytics/science majors (below right) to compare courses of study. Here is what I found:
They could not be more different. I cannot begin to tell you what someone learns in the course CSE 158 listed above, Data Mining/ML (machine learning) – and that is exactly the point.
As a leader charged with digital transformation, your organization needs the courage to choose a candidate with the background on the right and teach them what they need to know about accounting and finance business processes. There are plenty of people in your departments who know about those things. It will be uncomfortable, but that is what change requires, embracing discomfort and leading by example.
Now that you know what to look for, how do you find, attract, and retain these people? First, set a numerical target such as “50% of new hires will come from non-traditional backgrounds and sources.” To show you are serious, publicly declare this goal and tie it in some way to annual variable/incentive compensation.
To put this into action, a good place to start is with intern/new hire programs. Initiate contacts with universities and programs that produce primarily technical graduates. What I have found is that not everybody at these schools wants to be a professional engineer. Sometime in their second or third year, they come to this realization and shift into data science and analytic programs already equipped with a foundation of technical skills and a digital mindset.
Take your own Z People, finance/IT liaisons, BI managers, and whiz-kid analysts and make them responsible for recruiting, sourcing resumes/CVs and screening candidates. They know what you need and can articulate the opportunities that await should someone accept a position in the organization.
Also, have a plan for meaningful work/projects in mind that need the digital skills that the group is lacking. Remember to make sure that there are permanent positions available so promising interns can be offered full-time work when they graduate. Some universities even have internship/co-op graduation requirements so aligning with these programs can bring you a steady stream of talent that you can “try before you buy.”
This is just one idea, but the biggest thing is to start behaving differently or you will get the same result.
SSON’s 2021 state-of-the-industry report pointed out the “data-readiness gap” as an obstacle to achieving the next stage of value proposition for shared services. Within the report, almost 50% of those surveyed put the state of data (un)readiness down to lack of talent/skills, poor data reliability (who is going fix that?), and data not sufficiently organized/structured/digitized (someone needed here, as well).
I believe that the way to overcome these challenges starts with hiring staff who are “not like you.” Digital change leaders need to show the way by actively pursuing talent with different skills, backgrounds, and perspectives that can fill the “data-readiness gap.”
I am eager to hear others’ perspectives, however. What do you think is the best way to bridge the “data-readiness gap?”
Please comment below.