Ideas and insights for today’s people-centered leaders.

CULTURE

8 MIN READ

Notes From the People Cloud | Cracking the Code of Employee Scheduling

By Yustina Saleh and Chris Acitelli

An employee scheduling nightmare

I have a close friend who owns a number of daycare businesses that are part of a franchise system. The franchise provides employee scheduling tools and a myriad of software that helps franchisees with payroll, tech, benefits, supply management, curricula management and more. Every time I meet with my friend, I hear him complain about the operations in his business. “I stepped into one classroom, and there were 3 teachers and only 2 students. Why didn’t my director let two teachers go to help curb payroll expenses?” Another day he’d rant, “We were below ratio in this classroom, where are the floaters? This could cost me my business!.” Or, “They knew this teacher was leaving and waited until the last second to post her position. Now we are in a pickle.”

In this daycare, as is the case of any service providing businesses, operations managers end up hiring overqualified people for a very high premium or paying significant money in overtime that could have been mostly avoided. Even worse is when businesses turn down customers due to being understaffed. My friend shared with me several times how his managers turned down many per diem kids due to understaffing.


People are not robots

Here is another example. Consider a medical surgery unit, expecting to have thirty patients in a given day. Staffing and scheduling in this model are centrally managed by finance and they use a specific formula to estimate staffing needs. Typically, the number of patients will be estimated, then a budgeted hours per patient will be assumed and based on that number, staff members will be estimated for each shift.

Staffing and schedules are often developed by the finance department or by individual units that typically have a resident analyst to maintain these models with excel and other limited tools. There are significant overhead costs with analysts assigned to both build and maintain these models. While staffing and employee scheduling software exist, it is often expensive, difficult to customize, and not built for variabilities.


Causes of employee scheduling variables

First, variabilities related to the work volume or ‘demand’ are frequent. Even if the model is accurate in forecasting the number of patients, there are patient-related variabilities related to level of acuity of disease, cultural differences, comorbidities, functional abilities, and more. There is also variability related to the unit including access to information, technologies, unit governance, and bedside care hours. 

Secondly—and just as significantly—is the variability associated with staff or ‘supply’. These include variations in productivity in day shift versus night shift, shift duration, use of agency labor, skills and competencies, level of experience, turnover, leaves, and absences. Put simply: people are not robots. The same person can exhibit very different productivity levels depending on the team they are working with, their personal circumstances, the environment, burnout, fatigue, and so on. People have choices, feelings, and non-work obligations. These are rarely considered in standard staffing and scheduling models. They are often based on headcount and role, and little or nothing else.

quote from previous text block

Variabilities like these not only cause fluctuations in the need for staff, but their impacts can be seen in clinical and quality outcomes, employee and patient experience, and most importantly to the CFO: the bottom line. Excessive overtime or agency resource costs, missed revenue, or critical failures leading to reputation hits or even litigation can and often do result in big money losses. So, how do we figure out the right staffing and scheduling mix if things are constantly changing? And how do we quantify what happens when employees don’t stick to their schedules? What if they work late? What if employees who work 12-hour shifts are less productive than employees who work 10-hour shifts because they’re more fatigued? What would be the impact if only a few employees hoarded all the overtime available?


Get the right toolbox

Every operation involving employee scheduling with client-facing operations has the same complaint, sometimes quite often. Is this pain we’ve had for so long now considered normal?

Today, many client-facing operations have no way (or at best, limited, cumbersome ways) to schedule effectively or to systematically assess how well they schedule employees. There is also a lack of data on how well employees adhere to schedules. It’s difficult or impossible to directly connect the failure to schedule effectively and adhere to schedule on service levels, risk, patient experience or clinical outcomes, and the financial bottom line. In other words, there is a critical gap between the data we have on the workforce and important business outcomes. The People Intelligence Alliance (PIA) calls this gap the People Impact Gap. To close this gap, we need tools that enable users to understand:

  • Schedule adherence: Find employees who are most/least reliable at schedule compliance, and quantify the impacts, risks, and costs. Take action to measure and avoid downstream problems including poor service, financial and reputational risks, costly OT, and missed revenue.
  • Underbuilt or vacant schedule: If you’re consistently not meeting productivity or patient quality goals, or you’re incurring high overtime and agency costs, it’s likely because your schedule is not sized right and filled. Underbuilding or vacancies cause you to start every day short, and recovery can be difficult and costly.
  • Overcoming unavoidable schedule gaps: The schedule is your target. Absences happen naturally even after you solve adherence issues. Knowing the target and the gap, you can fill and optimize your staffing strategy to close that gap at lowest cost through float employees, contingent staff, gig workers, etc.
  • Connecting people data with business outcomesSometimes businesses achieve the first three capabilities through traditional scheduling software, but fall short with perhaps the most important piece—connecting that people data (scheduling and compliance) with business outcomes, such as reimbursements and clinical outcomes.  Visier can connect these to provide more and deeper insights as to where the problems are and what costs and risks they are driving.

The formula is not a magic wand

It’s surprising that available planning and employee scheduling software has largely not figured out a way to manage these problems efficiently. But perhaps the problem is that users are looking for the missing keys inside the house when they were actually lost in the street? These planning and operations tools are mostly top-down and focused on numbers—volume of work and headcount required to deliver the work without considering the people aspect of the work. 

Whenever I present this concept in relation to employee scheduling, I get asked, “What’s the magic formula to do this right?” And the truth is, the magic formula is not really a formula at all. Rather than a static algorithm, we should look for a way to detect patterns as they evolve and introduce actions that dynamically address and respond to these patterns with the goal of optimizing specific outcomes. For example, ask, “What schedule should I put in place to minimize service delivery failure?” A service delivery failure event or cost of service delivery failure would be the business outcome you are trying to predict. Then you can bring in time series data related to scheduled hours, actual hours, turnover for individuals, seasonality, overtime trends, shifts for individuals, teams, collective experience of the team, and so on. Use predictive modeling then, to optimize scheduling for both teams and individuals in order to minimize service delivery failures.


New technology solves an old problem

The task is often much bigger than what a single analyst can manage. It requires technology with advanced AI capabilities, full transparency, ability to customize, and user-friendly configuration to be able to adjust the targets or outcomes for optimal performance. A data warehouse to bring all relevant data in one box is simply not enough. There are assumptions that could be built into each data element and system, which a simple predictive model isn’t able to detect. Each of these individual data elements were introduced for a specific purpose—probably reporting—and using that data element for optimization requires significant amounts of data harmonization and curation. That is not a task for a data warehouse.

quote from above text block

Neither will a simple data visualization tool help you solve the scheduling problem. Your question and the optimization goal will need to be adjusted for your business needs, which can change every day. This means this new technology must actually help you understand the questions to ask each day, and then find new ways to answer those questions. Finally, when the meaning behind the data is harnessed, and the right questions are asked, with the power of a dynamic and configurable predictive model, you can truly orchestrate action. For example, an action could be: 

“I can’t put all of my less-experienced team members on the same shift, even if the staffing model allows for that. To reduce risk and also maximize opportunity for learning, I must spread the more experienced employees across shifts.” 

Or:

“There is seasonality and also day-of-the-week factors when team members tend to call off sick. I will need to build that pattern into the schedule”

Or:

“Nurses who are hired as contractors without benefits are much more likely to quit, and often with short notice. I will hire fewer of those, but will build in more cushion in the schedules if the only option is to fill it through contract nurses.”

There are so many options, but it all starts with truly understanding the cost of people related variability, and working around that rather than assuming people risks are random events. 

These are the kind of problems that only People Cloud powered by Visier can help you address. Interested in learning more? Schedule a demo today.

About the authors:

Yustina SalehYustina Saleh Ph.D.

Yustina has been on a quest for connecting people and value for over 20 years. Her life goal is to help people and organizations unlock their unique niches and then find and be found by their perfect matches. As Visier’s VP, Research and Value, she’s building a platform that connects people and work data with business outcomes to maximize people impact.

 

Chris AcitelliChris Acitelli, Director, Solutions Management

Chris has been bumping around the people analytics space since before that was a thing. He started in call center workforce management before graduating to Workforce Intelligence and Planning through stints at Healthcare, Logistics, Banking, and Telecom companies. He’s built many staffing models and dashboards, and was a Visier customer as well as a ‘manual builder’ before joining the company as a Solution Management Director. Chris is working to provide more value to Visier customers in those industries he knows best.

About the author: Visier Team

People-centered ideas and insights by the editorial team at Visier.

Be the first to know!

Never miss a story! Get the Outsmart newsletter.

Related Articles