Collection No 6
Tools and processes for taking back the work week.
Information workers waste an inordinate amount of time orchestrating work rather than doing work. Instead of creating new content to drive our businesses, organizations, and missions forward, we spend our time looking for information and people, and then connecting and coordinating them to ensure that good decisions are made, or that other people can do their jobs. It is all terribly inefficient.
There are some obvious moments when this inefficiency is exposed. For example, the technology tools that support our work—from conference bridges to projectors to screens—often fail to function properly, and we waste time fiddling around with them. But there is a deeper, more insidious inefficiency at the heart of information work, and most information workers are not even aware that we have a problem. Our language betrays our ignorance. How often have you heard people say, “We need to get on the same page,” or “I’ll try to get some time on your calendar?” These expressions are examples of information workers orchestrating work rather than doing work.
Good statistics on this topic are rare. The research of software companies including Doodle and Atlassian suggests that information workers spend around two hours per day looking for information. We spend an average of 1.5 hours per day in meetings and just under an hour per day scheduling meetings. According to McKinsey & Company, we spend two hours sending and responding to email. Add these tasks up and they take a total of 6.5 hours per day. If we are generous and count half the time spent in meetings as productive content creation rather than alignment, it still means that 50 to 60 percent of an information worker’s day is spent orchestrating work.
Information work needs its industrial revolution. We are not, of course, suggesting that we need to move workers into a factory setting—indeed, the “cube farms” of the corporate world are often part of the problem. Rather, information work needs its version of the automation that enhanced the productivity and output of individual craftspeople in the industrial revolution. Admittedly, this shift was also accompanied by painful transitional unemployment, social disruption, and environmental degradation, but over time, the industrial revolution lifted millions out of poverty and triggered a step-function in up-leveling humanity. Done right, the impact of automating the orchestration of information work will be just as dramatic.
The following products, services, companies, and approaches—while not a complete solution—indicate that we are moving toward this goal and provide promising signposts to the future of information work.
Content creation is a free-ranging activity that is defined not by tools, but by the ability to connect information in different forms. Yet today we are forced to work within the confines of software capabilities, and that constraint shapes the way we approach content creation. Most applications are loaded with features that are rarely all relevant at the same time. Moreover, in the enterprise context, information workers can hardly use content consumption software to create anything new. Consider the plight of the researcher who finds various charts, figures, and data in PDF format and must then use various tools to recreate or reference each type of information as she creates unique content. The researcher will jump from application to application without questioning that routine. Why?
A more efficient approach would be for the software to arrange itself around the content creation activity at each specific point in time, adapting to personal workflows and contexts. In this scenario, the software would learn from the data in the creation process instead of just following instructions. Today we have an analogous experience with predictive text engines, which recognize patterns in the way we write. They suggest, with increasing accuracy, complete words or phrases as soon as we type familiar letters. Using a similar logic, programs originally packaged in different applications would emerge into the content creation process as individual or recombined services at the precise moment when they are needed. Such an orchestrating software layer would be infused with predictive logic and learning capabilities; it would serve the information worker before serving applications.
A few technologies are charting a path toward this vision. Products such as IFTTT and Atooma allow users to choreograph and automate the interaction between programs and services according to personal preferences. Microsoft first enabled users to embed a spreadsheet into PowerPoint and work on it without switching to Excel, and later developed live tiles in Windows, which partially reduced the need to jump from application to application. VMware runs applications from different systems in a unified work space. Apple introduced uninterrupted workflows between devices with Continuity, and with iOS 8 moved toward a more personalized software experience by supporting the integration of functionalities from a broad range of applications into a single application. Together, these technologies offer glimpses of the software metamorphoses required to meet the needs of the modern information worker.
Knowledge management is a huge challenge for information workers. People join and leave organizations so frequently that institutional memory is fleeting. Indeed, project-based work in which people come together temporarily and then disperse is challenging the very notion of institutional memory. In larger firms, different groups of information workers may tackle the same problem without being aware that others are doing the same.
Managing knowledge to give people the information they need when they need it is the baseline requirement for efficient knowledge work. Offering knowledge multipliers to information workers—such that they are armed with information they did not even know would help them—should be the ambition of those interested in moving beyond the baseline.
We see hints of this at the feature level of some emerging offerings. For example, frog client Unify recently launched its Circuit product, which contains two knowledge multipliers: Thought Trails and Intelligent Spaces. The communication and collaboration tool analyzes content and communication patterns to suggest connections with others in the firm working on similar challenges. Conference calls are transcribed and made searchable, together with shared documents, allowing the system to recognize patterns across the organization and to offer insights. The information worker does not have to go looking; the relevant content is curated and offered up at the right moment. Another example comes from the work of Quid. This company’s intelligence platform makes connections across complex data sets to enable the fast and comprehensive generation of insights.
We want to take this process to its logical conclusion: knowledge multipliers will be tools capable of extending the intellectual capacities of information workers. They will not just optimize the process of collecting and making sense of information, but will fundamentally aid in the creation of new information at unprecedented speed, quality, and volume.
Many recent frog projects involve thinking through products and services that take advantage of sensors and sensor networks to enhance human experience. A great example in the consumer space is the Disney MyMagic+ ecosystem, which uses a wristband to allow park guests to interact with the environment around them. The wristband acts as a ticket, FastPass to rides, wallet, and key to unlock hotel doors. But more than that, it allows Disney characters to greet guests by name and interact with them in a personal way. It is tailoring the environment to create an individualized experience.
Another great example is the use of sensors in cars to adjust an experience. Using sensors in the seat and steering wheel, or coupling facial recognition technology with emotion mapping, allows us to build cars that calm us when we are stressed or wake us up when we are tired. There are many other examples and use cases across multiple industries. This movement is characterized by widely distributed sensing technology, and it is ripe to be applied to information work.
What if we could draw on our physiology, emotional state, and mood to determine the optimal time to perform various tasks? At frog, we know that our best ideation occurs when participants are well rested, calm, and focused. What if our task lists for the day could adjust based on biometrics and historical information on optimal performance?
What if the entire firm was sentient? By combining and analyzing data from sensor networks in the physical environment, with awareness of the content being generated by information workers at any given point in time, we could create a working environment that is akin to a sentient being and capable of adapting to the conditions of its inhabitants.
At frog, we move ourselves to various locations around the work space based on our individual work styles and the particular task at hand. For example, in our San Francisco studio, we have the Zen Lounge, which contains both seated and standing desks equipped with noise-canceling headphones, where we go to complete “heads-down” tasks. Other work areas are more collaborative and noisier. What if spaces adjusted to the work and people using them, instead of the other way around?
Environmental sensors, knowledge multipliers, and software metamorphoses will redefine the way workplaces and tools support the activity of information workers. Done right, this revolution has the capacity to dramatically increase the quality and productivity of information workers. It will free them to focus on the creative tasks that add the most value to their organization, while eliminating the frustrating, time-consuming aspects of today’s information work. This is an opportunity to advance the future of work, which, like the industrial revolution, promises exponential impact for businesses and workers alike.
Tim leads a global team of business and product strategists who work alongside frog designers and technologists to bring game changing innovations to market. He has worked in Silicon Valley for 15 years in a variety of product, strategy and marketing roles.