What is an Information Worker?

What is an Information Worker?

What is an Information Worker?

When Peter Drucker originally articulated the idea of a “knowledge worker” in 1959, he was proposing a classification with the primary goal of describing the work of people who applied knowledge directly and in a unique way, to the tasks assigned to them. One important differentiator of the knowledge worker was that he or she owned their means of production—which literally means people have brains, and they bring their brains to work. Unlike blue-collar workers who do not own the factory equipment they use to produce products, knowledge workers own the knowledge and skills they apply to create value. Some use the term knowledge worker as a synonym for professional, which now accounts for roughly twenty-five percent of the workforce in industries like financial services, high-tech, healthcare, pharmaceuticals, and media. Knowledge work, in this now-classic definition, is too narrow to define the type of work that have evolved over the last thirty years.

As computing technology infused into organizations, it became a new tool for understanding an organization’s data. In many cases, it did little more than consolidate data, and make the data more presentable to knowledge workers. Over time, though, computer programming became more sophisticated. Some of the knowledge of knowledge workers found its way into computer programs and computers became more capable of applying knowledge to data without human intervention. This development started to spread knowledge through the organization, but usually in very limited, and very specific ways. This was the first instance of information work: people without fundamental knowledge were able to apply the knowledge of others to data, and act on those insights without a direct connection or consultation with the holder of the knowledge.

An Information Worker is a person who uses information to assist in making decisions or taking actions or a person who creates information that informs the decisions or actions of others.

The application of computing power to data was also becoming more accessible, as programs developed that allowed non-computer specialists, usually knowledge workers, to create documents and databases that codified their knowledge. As these applications were shared, they too added to the disbursement of knowledge throughout organizations, but specialized knowledge remained far from pervasive. Knowledge work had expanded from those who knew personally, to those who could leverage knowledge embedded in computer systems.

As the personal computing revolution took hold, it became apparent that work itself was changing. The percentage of people working with data was increasing, and was no longer limited to the creation, collection, and forwarding of that information to “knowledge workers.” Data was staying local and being used to help workers of all types make better decisions about their work product, in real-time. These workers did not have throngs of knowledge workers to send their work to for interpretation and augmentation but rather used the knowledge that was now embedded in software to filter, organize and garner insight from the data most relevant to them. These workers became known as information workers. An information worker, therefore, is a worker who uses information to assist in making decisions, taking actions or creating information that informs the decisions or actions of others.

Let us step back, however, and use manufacturing to explore the evolution of information work and its relationship to business operations. It can be argued that blue-collar workers applied knowledge all the time as well. They just did so in ways that increased the value of physical assets rather than information or financial assets.

A knowledge worker in a front office would be hard pressed to understand the kind of work that takes place in a sheet metal factory, or the knowledge required to transform sheet metal into products. The front office worker may have clear visibility into the schedule, the costs, the status and other information elements of the factory, but they have no specific knowledge of the work being done.

If you think about a sheet metal worker, they have very deep knowledge of the material they work, and the machines used to shape the material into products or components of products. A knowledge worker in a front office would be hard-pressed to understand the kind of work that takes place in a sheet metal factory, or the knowledge required to transform sheet metal into products. The front office worker may have clear visibility into the schedule, the costs, the status, and other information elements of the factory, but they have no specific knowledge of the work being done. This represents a two-tiered, hierarchical information model for the factory. One layer is specific and local, in that the manager and the sheet metal workers understand the knowledge required to transform raw materials into products and components. The other layer is abstract and represented in a language knowledge workers use to understand the factory. They treat the shop floor not as a physical location, but as a component of the business’s information model. In this example both of the groups, those on the factory floor applying knowledge to material, and those in the factory’s front office applying knowledge to schedule and cost control, are knowledge workers, and the interplay between their information makes them information workers in general.

hand pushing on touch screen interface


Knowledge is specific, and information is general. Both of them use the same information about dates, schedules, plans, and costs. Updates to status come from the factory floor to planners in the front office who can anticipate material shortages, or reschedule the factory based on new demand. And the manager of the sheet metal shop reacts to the information coming from planners to create his or her daily schedule. That is information work. The knowledge work of both remain as well, with the planners applying knowledge to optimize factory operations in total, and the manager applying knowledge to make sure products are produced with high quality, high-efficiency in a very safe and well-maintained environment. Those specific examples of knowledge would rarely be exchanged between the parties, whereas the information about scheduling, status, and cost, flows freely between the two, even though it may be applied in different ways, with different levels of abstraction.

At a higher level, current efforts to distribute work in a way that reflects economies of scale, or to leverage lower-cost facilities and labor are the result of knowledge work applied at the abstract level of the information model. The actual work still requires local knowledge. That manufacturing knowledge remains consistent and local if it is applied in Detroit or in Bangkok. The more abstract information treats both locations as part of an overall business model that represents global production goals, including cost, transportation to various markets, and other factors. The differentiation between knowledge work and information work remains consistent even when the definitions are applied to modern global enterprises.

Like any classification, information work begs for a more granular taxonomy, but it is at the highest level of abstraction that the profound implications become apparent. Information workers now have access to vastly more data and information than even the most astute knowledge worker had in 1959, and they have become better consumers of this information. This has precipitated a more localized and distributed view of decision-making, which has lead to organizations that act more like networks, than the previous model that relied on hierarchies fashioned on a command-and-control model.

In fact, it can be argued, that knowledge work as a job classification was a reaction to the increasing amounts of data available in organizations, and the lack of a means to process that information. Information work focuses on a distributed model for empowerment and trust that sees the organization as a self-sustaining network with information feedback loops that reinforce positive, goal-oriented behavior.

Information work will become the predominate attribute of most occupations as work is transformed by the availability of data, and the ability to better understand that data so that local decisions can be better informed. The factory manager has more information about the factory, on a number of dimensions, from quality, to supplier relationships than ever before. And front office workers have more information about the overall business. This democratization of information has lead to networked organizations where decision-making is more distributed, and where “management” often moves from day-to-day concerns around operational details to a role where they ask deeper questions about direction, vision, and values.

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Information work is most meaningful as a transformative idea that has profoundly influenced the way most workers perform their jobs, giving them ever-increasing visibility and insight into the world that affects their jobs, and even greater control over how, when, and where that work takes place. The evolution of computing from “factory” data processing with mainframes and mini-computers, to personal computers owned by knowledge workers, makes the personal computer an extension of human capability. Gardeners and plumbers also own their means of production as they arrive at the job site with their trucks and tools. When the information worker arrives at work (or works where they arrive), they turn on their computer and unleash the power to communicate, to assist in the analysis of information, and have instant access to a wide variety of information sources over networks. The system acts as an extension of the employee by reflecting the way they work in terms of organization of information, bookmarked and replicated sources, and various processes and tools the information worker has collected that make him or her more effective in the work they do. The information worker can be seen as the primary means by which the raw material of data is transformed into information so that actions, including decisions, can be made using the information as it has been interpreted.

The effects of information work can be seen in four categories or trends which are, in many ways, implications from the evolution of work from a local perspective with limited knowledge applied specifically, to better informed local knowledge informed by a global context, and ever-increasing visibility of the connections between work, policy and practice, that allows the organization as a whole to make better-informed decisions.

Reflections on Definitions

The relationship between knowledge and skill was drawn too narrowly in the past. Skills were seen as very local and very contextual. One could not broadly apply skills, but they could broadly apply knowledge. Information technology has blurred that distinction if it existed at all because even people who focus on the output of a single machine can clearly see themselves as part of a larger ecosystem within an organization. They feed into upstream processes and are the recipient of downstream processes. They are no longer limited by management communication as the sole source for information about their job and their organization. Information workers may belong to communities of practice or directly interface with quality system or order systems that give them broader insight into how their work affects others. All of this means that machine operators, call center operators and others who may appear to be limited to a task are now have more information and context to inform their choices, and they know more about how their work affects wider processes. This should make information workers integral factors in the decision processes of the organizations that employ them.

A call center operator dealing with an exception is a good representation of the modern information worker. Although a script exists that guides the call center operator through a process, many times the existing information does not reflect the experience of the customer. Those call center employees empowered to seek customer solutions and provided with the right information technology can easily connect with experts, management, read additional policies or work with their communities and use collective knowledge to make better decisions. Those employees are can resolve exceptions more effectively than employees constrained by systems and policies that limit their ability to discover and apply information that may help turn a complaint into a satisfied customer. If you add additional proactive assignments, such as cross-selling, the isolated call center operator clearly becomes a person who applies knowledge to data on behalf of the customer and turns that data into information. He or she acts of information, makes complex decisions, and communicates information and perspective to customers, peers, and management. These information workers exhibit many of the traits associated with knowledge workers without the prerequisites required by Drucker. Information workers are best defined by what a person actually does within the firm, not by limitations and false distinctions of education or placement. Technology has provided many workers with the ability to enhance their skills to the point that they make much larger contributions to their organizations that they would have in the same job twenty years ago.

If we replace knowledge work with the broader definition of information work, organizations must then consider the need to concentrate their productive workforce on areas that contribute value or run the risk of a reduced competitive position.

If we replace knowledge work with the broader definition of information work, organizations must then consider the need to concentrate their productive workforce on areas that contribute value, or run the risk of a reduced competitive position. In the information work, economy organizations must understand the information work that is important to their success, and optimize their processes, both formal and informal, to leverage the people who can transform data into information in order to transform those activities into business value.

The semantics of any classification system can be argued, but the most important of classifications in this discussion is the one from which all others proceed: people. People make businesses what they are. They build customer relationships, mitigate risk, and optimize business processes. People may have specialized knowledge and apply specialized tools in narrow circumstances, or they may have access to diverse and far-reaching information sources that they use to gain insight into broad business questions. No matter their role, people’s ability to use knowledge to transform data into information, and their ability to use software to make that process ever more efficient, is the means by which modern organizations will succeed.

People, empowered by software, organize information, discern patterns and communicate their findings—this places them at the pivotal center of today’s work, and tomorrows. People are the means by which organizations adapt to the changing currents of global trade, help minimize the burden of regulation, integrate and leverage technological innovation, meet customer expectations, and adapt to shifts in the demographics, distribution, and attitudes of the workforce itself.

Information technology has given today’s workers the ability to look beyond the confines of their own work and see the relationship between what they do and what the organization endeavors to become. This gives the information worker a unique ability, compared to workers in the past, to make better-informed decisions, and take more decisive action. Empowered with the right information and the right tools to apply their knowledge effectively, people create the context for the next generation of innovations in organizations ranging from civic and national governments to local proprietorships and multinational enterprises.

Bibliography and Suggested Reading

Drucker, Peter F. Managing in the Next Society. Truman Talley Books. New York, NY. 2002.

Spira, Jonathan. Managing the Knowledge Workforce. Mercury Business Press. Yorktown Heights, NY. 2005

Davenport, Thomas H. Thinking for a Living. Harvard Business School Press. Boston, MA. 2005.

Pink, Daniel H. A Whole New Mind. Riverhead Books. New York, NY. 2005


Daniel W. Rasmus

Daniel W. Rasmus, Founder and Principal Analyst of Serious Insights, is an internationally recognized speaker on the future of work and education. He is the author of several books, including Listening to the Future and Management by Design.

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