Abstract:
The authors studied 20 teams, totaling 137 users, across three Fortune 500 companies for up to five weeks. They found workers toggled roughly 1,200 times each day, which adds up to just under four hours each week reorienting themselves after toggling — roughly 9% of their time at work. While many companies may write this off as the cost of doing business in a digital environment, more often it’s an active choice that companies and managers are making about how work is done and the programs that are used to do it. As such, managers need to realize that simply adding people to cover for bad processes won’t fix the problem, look for places where the design of work is causing the most friction, and rebalance people’s workloads. Leaders need to rationalize the cost of acquiring or building better software solutions, focus on user experience, and invest in building a work graph to better understand their employees’ journeys through their work.
How many times do you think you toggle between applications over the course of your day? For digital workers, bouncing between applications has become an inescapable part of work — hitting Alt-Tab comes as naturally as breathing.
It’s not hard to see how we got here. As business needs evolve, new applications are brought in to address them, and CIOs and managers struggle to retire old ones and keep numbers down. In large organizations, there can be thousands of applications, and smaller ones regularly have tens if not hundreds. As a result, employees spend their days constantly switching from one to another.
Consider an example from a Fortune 500 consumer goods organization we studied. To execute a single supply-chain transaction, each person involved switched about 350 times between 22 different applications and unique websites. Over the course of an average day, that meant a single employee would toggle between apps and windows more than 3,600 times. That’s … a lot.
This kind of toggling is often dismissed as simply “how we work now,” even though it’s also taxing for people and a waste of time, effort, and focus. Yet these trends are likely to continue or get worse in an increasingly digital and remote work world. This should give companies pause. The cost of this way of working may be higher than they estimate, and if they recognize that, they may be able to find a better way of working.
The Toggling Tax
When a user switches from one application to another, it is not just the mere physical act of pressing keys to switch that costs effort. It takes time to adjust to the application, its semantic context, and purpose after a switch — users need to get their bearings, even if they were just looking at it. For example, when you switch from an email to a spreadsheet, the two interfaces, layouts, and purposes are very different. Before you’re prepared to get on with the task you switched over to do, it takes a moment to quickly adjust to the spreadsheet.
This readjustment takes a toll. Psychology and neuroscience have shown that jumping between tasks — also called “context switching” — is cognitively taxing. We find that even switching or toggling between two applications equates to context switching. Excessive toggling increases the brain’s production of cortisol (the primary stress hormone), slows us down, and makes it harder to focus.
What we wanted to measure is: How much time and energy is wasted when you add all these moments up?
Using a work graph — a piece of software that reveals how teams interact with applications to get their work done — we performed a ground-up measurement of the cognitive effort cost of switching. To do this, we studied 20 teams, totaling 137 users, across three Fortune 500 companies up to five weeks, for a data set of 3,200 days of work. Most of these teams worked mid- or back-office jobs in finance, HR, supply chain, recruiting, inventory management, and the like. Looking at this data, we measured how much extra time it took for a user to engage with the next step in their task after toggling — how long it took for them to reorient and figure out what they should do next.
We found that, on average, the cost of a switch is little over two seconds and the average user in the dataset toggled between different apps and websites nearly 1,200 times each day. That means that people in these jobs spent just under four hours a week reorienting themselves after toggling to a new application. Over the course of a year, that adds up to five working weeks, or 9% of their annual time at work.
The Cost of Doing Business
Is this really a problem, or is it just the cost of doing business in a digital environment? To shed light on that, we also took a closer look at how people worked and measured the time spent between two successive toggles.
We found that after 65% of switches, users toggled to yet another app less than 11 seconds later. In other words, the time spent on an application is not significantly higher than the tax paid for toggling over to it. The result is that users are being asked to constantly refocus, and their attention spans are fragmented, which leads to them being depleted. This state of distraction typically occurs due to poor work design and a plethora of applications. Basically, how we work is itself a distraction.
For most employees, there isn’t an obvious way around ping-ponging between documents, websites, and apps — it’s just how the work has to be done. Most enterprise applications weren’t designed to connect to each other, which means that people operate in “swivel chair” roles, fetching and transforming data from multiple applications and then submitting data into other systems. A sizable part of their jobs is to act as the glue between disparate applications. This is a common pattern of work in almost every organization in the world, regardless of industry or size. Processes and tasks that people execute are designed to span multiple applications and hence the very nature of work today requires such constant toggling.
But it doesn’t have to be this way. Managers and leaders can — and should — take action to improve the situation.
What Managers Can Do
To be sure, we are not saying all toggles are bad. It’s not plausible to build an all-encompassing enterprise application. But there are several lessons managers can take away from these findings.
Throwing people at the problem isn’t a solution. Of course it’s possible to hire people to act as glue between disparate IT applications, but doing so just papers over the fact that fragmented IT applications are the root cause — and increases the cost of not fixing it. Today, the way work is designed inherently causes people to pay the toggling tax, lose focus, and get distracted. If you choose to deal with this problem by adding more people, then factor in the reality that they are suffering from a poor experience at work which also affects their productivity.
Look for places where design of work is causing friction. A proxy for finding hotspots where the toggling tax is high is to find teams doing work with several applications. For such teams it is like that investing in improving the design of work and reducing the application footprint will streamline their work experience.
Rebalance workloads. People who are engaged in work where they are constantly switching between applications are more likely to be bored and distracted. Hence, they are likely candidates for attrition or being disengaged with work. Nobody really wants a job where all that they do all day long is just repeatedly switch between disparate applications. Consider load balancing such work patterns across the team.
What Leaders Can Do
Members of the C-suite have even more power to make change. It’s important for them to recognize that employees can no longer be aggregated and averaged into a handful of employee personas — proxies that companies use as stand ins for large groups of employees when designing work and systems. Instead, personalize the design of modern applications to all users in the organization versus just a few select power users (as is the case today). Specifically:
Rationalize the cost of introducing new applications in the landscape. Approve releases with actual hands-on users (instead of the nominated few power users) at every stage of software development. For example, a Fortune 500 retail pharmacy chain introduced a web-based pharmacy adjudication system to replace an old mainframe system — only to realize that most of their busy pharmacists were so used to the mainframe’s interface and response time they didn’t care for a much cleaner web interface. Speed and reliability were more important to them.
Lead with user centricity and user experience. Ideal applications are designed to be seamless, encourage users to focus, and minimize the toggling tax and digital distractions. To design such applications, charge your user centricity (UC) and user experience (UX) teams to lead design of new processes and systems and to include the multitude of user personas vs just the few in their design process.
Invest in building and nurturing a work graph. Consumer brand companies invest millions of dollars plotting the longitudinal consumer journeys and consumer graphs with millions of specific data points on how consumers act, interact across channels, apps, and physical environments. They then spend hundreds of millions of dollars pushing the right messages and interactions, nudges for a seamless shopping experience.
Leaders can learn from them to do the same for their people — their most productive assets. Each employee has millions of touchpoints and deserves the same personalization and attention. We urgently need to build the longitudinal employee journey for all companies — the work graph to be precise — that unlocks unique insights and enables continuous digital problem-solving. For example, integrating purchase order approvals on Outlook email was not in the first release of most procurement software but this is now a standard feature. The ideal situation is to make improvements weekly or monthly. A work graph would enable faster problem finding and solving.
N.R. Narayana Murthy, the founder of Infosys, once said: “Our assets walk out of the door each evening. We have to make sure that they come back the next morning.”
In the age of high attrition, it’s vital for leaders to prioritize improving employee experience as much as they are concerned about growth, customer experience, and profits. The toggling tax is an example for the need for empathy for how people experience work. Such empathy, backed by data from the work graph is likely to scale and be the best bet that the most important assets come back next morning.
Copyright 2022 Harvard Business School Publishing Corporation. Distributed by The New York Times Syndicate.
Topics
Technology Integration
Performance
Systems Awareness
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