One specific arithmetic issue has plagued organizations of all sizes and sectors worldwide since the industrial revolution. If I'm a financial advisor, there are essentially just two data points I need to determine whether or not my firm can give the necessary results to customers: How many hours do I require to complete the assignment, and how much time do I have?
Many teams are randomly set at 12 persons for any reason. That implies most managers operate under the assumption that they have a dozen employees to do any assignment, which indicates they have twelve people's time to do so. And, when everything is said and done, managers are failing to solve the time challenge (at least, not in a way that optimizes manpower and resources). They either aren't given enough or have an excessive amount of time.
Part of what complicates these decision-making challenges is that time is measured in multiple currencies. Assume you're a manager in charge of a team that makes widgets. One widget takes three hours to complete by one person. There are 600 widgets being produced. I'm making 20 widgets every day. I have 120 employees. Eighty of my workers put in eight-hour days. Forty people work four-hour days on a part-time basis. So, do I utilize "widget" hours to compute productivity or determine how long it takes to do the work? Shift hours? Working part-time? Working full-time days?
Add to this the following external factors that influence baseline man hours: Is anyone out of commission this week? Are you on vacation? Attending a widget-making convention? How many widget producers work remotely and how many work in person? Do all widget producers work at the same rate? The question of how much time is required and how much I have has suddenly become an extremely difficult math problem (not to mention a major headache) that is impeding every decision execution.
We've all felt the effects of team time management misalignments as customers. At the airport, for example: When multiple flights are scheduled to depart or arrive at the same time, there are frequently insufficient TSA agents or open lanes to accommodate all of 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 that can be hours long, with travelers becoming increasingly anxious and cranky. TSA agents may be staffing near-empty stations at off-peak hours (such as late at night) with only a few planes coming or departing, seeing few or no people. Everyone can agree that both of these scenarios are less than ideal.
These issues get significantly more complex when we consider a huge back office like a healthcare organization or a bank, which requires 24-hour operation and many systems with hundreds or thousands of moving elements (and human beings) that must be coordinated. Consider processing a health insurance claim, where a patient's treatment, payer, plan, deductible amount, and several other parameters must all be appropriately recorded for in order to create an accurate EOB. The operational challenge of determining how many hours are required against how many hours are available gets extremely difficult. And faulty or delayed products generate a slew of problems for patients, providers, and healthcare institutions.
The majority of firms have invested in two sorts of solutions to team time problems: Human capital management (HCM) software systems, which cover personnel, payroll, holidays, and so on, and business process management (BPM) software systems, which deal with business operations. Huge investments have been made in both HCM and BPM technology in recent years. However, many firms struggle to extract data from these platforms and bring it together. Often, the problem isn't a shortage of knowledge as much as it is an inability to synthesis different streams of information into meaningful, process-improving implications. (And, more frequently than not businesses are juggling six separate Excel spreadsheets in an attempt to make sense of these many data sources, which works about as well as one would anticipate.)
Managers must be able to mix numerous data streams (sometimes in different forms, "currency," and available across different time periods) as well as collect and exploit the data gathered from them in order to make optimum choices. These two things add up to gold. The good news is that team time management has become simpler in recent years as a result of the use of technology that integrates HCM and BPM data. With the help of these more strong technology solutions, managers may not only tackle team time issues in one location, but also load balance with team members working in several places Leveraging the value of these data solutions is quickly becoming a need for forward-thinking companies, particularly in an era when time problems may be complicated even further by hybrid and remote work situations.
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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