Spencer O’Leary is the Chief Executive Officer of ActiveOps North America.
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As early as the industrial revolution, one particular math problem has faced businesses worldwide, of all sizes, in all industries. If I'm a manager in a business, at the end of the day, there are really only two bits of data I need in order to know whether or not my company can deliver the desired outcomes to customers: How many hours do I need to get the work done, and how many have I got?
For whatever reason, many teams are arbitrarily set at 12 people. That means most managers are working with the idea that they have a dozen people to accomplish any task, which—for operational purposes—means they have a dozen people’s time to do so. And when it comes down to it, managers are not succeeding in solving the problem of time (at least, not in a way that optimizes manpower and resources). They either don’t have enough time, or too much.
The Problem Of Different Currencies
Part of what makes these decision execution problems so convoluted is that time is measured in different currencies. Say you’re a manager whose team produces widgets. One widget takes one person three hours to complete. There are 600 widgets in the process. I’m completing 20 widgets a day. I have 120 workers. Eighty of my employees work eight-hour days. Forty employees are part-time, working four-hour days. So to calculate production, or figure out how long it takes to complete the work, do I use “widget” hours? Process hours? Part-time worker days? Full-time worker days?
Add to this outside considerations that impact baseline man hours: Is anyone sick this week? On vacation? At a widget-making conference? How many widget-makers are teleworking, and how many are in-person? Do all the widget makers work at equal efficiency? The question of how much time is needed, and how much I have, has suddenly become an incredibly complex math problem (not to mention a massive headache) that’s getting in the way of all decision execution.
The Impact Of Team Time And Resource Management Breakdowns
On the consumer end, we’ve all experienced the impacts of team time management misalignments. At the airport, for instance: When many flights are due to depart or arrive at the same time, there are often not enough TSA agents or open lanes to accommodate all the travelers going through check-in and security on one end, or customs and passport control on the other; as a result, there are lines—sometimes hours long—with travelers becoming progressively more anxious and cranky. However, at off-peak hours (such as late at night), with only a few flights arriving or departing, TSA agents may be manning near-empty stations, encountering few or no travelers. Everyone can agree that both these situations represent less than ideal management of team time.
These problems get even more intricate when we’re talking about a large back office for a healthcare company or a bank, which relies on 24/7 operation, and multiple systems—each with hundreds or thousands of moving parts (and human constituents)—that must be in coordination. Take processing a health insurance claim, for instance, where a patient’s procedure, payer, plan, amount of deductible, and various other factors all need to be correctly accounted for to generate an accurate EOB. The operational problem of how many hours are needed and how many hours are available becomes incredibly complex. And error-ridden or delayed products cause all kinds of issues for patients, providers, and healthcare facilities.
When Traditional Solutions Fail
There are two types of solutions that most businesses have invested in to get an answer to team time problems: Software systems that handle human capital management (HCM), which includes employees, payroll, holidays, etc., and systems that manage business process management (BPM), which deal with business processes. In recent years there have been huge investments in both HCM and BPM technologies. But many businesses struggle with getting the data out of those systems and pulling it together. Often the issue isn’t so much a lack of information as an inability to synthesize multiple streams of information together to yield meaningful, process-improving implications. (And, more often than not, we find businesses juggling six different Excel spreadsheets, trying to make sense of these different data streams, which works out about as well as one would expect.)
Managers need to be able to both combine different data streams (which are often in different formats, different “currencies” and available over different time horizons) and also capture and leverage the data drawn from them to execute optimal decisions. These two things together equal gold. The good news is that team time management has gotten easier in the last few years due to the adoption of technology that integrates HCM and BPM data. With the benefit of these more robust technological solutions, managers can not only resolve team time problems in one place, but load balance with team members working in multiple locations. Leveraging the power of these data solutions is becoming a necessity for forward-thinking companies, particularly in an era when time problems may be complicated even further by hybrid and remote work situations.
More Solutions, More Demand
There’s a certain irony: The more technological capability we have to deal with variables, the more choices humans want. One of the things that makes the problem of team time management ever more complex is that, as humans, we want more flexibility, we expect more creativity, and we demand an ever higher standard of convenience (from health care and financial systems, in particular.) For instance, it used to be that on Christmas day, things were closed—but now we expect to be able to do our banking in the middle of Christmas dinner from our smartphones. As consumers, we live in this 24/7/365 world: we want everything delivered in 20 minutes. So, managing the right people in the right place at the right time is harder and harder to do. Whenever we invent the technology to deal with these demands, as consumers, we think of two more “wants”—and the problem has to be reinvented again.
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