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In this whitepaper:
Research has identified the top six organizational management factors that powerfully correlate to the performance of knowledge teams. These findings are the best available evidence on the topic of knowledge worker performance.
What you will learn:
- Why measuring knowledge worker productivity is a challenge
- How these Six Factors relate to the performance of knowledge worker teams
- What an organization acting on these findings should consider
- What these findings mean for the future of workplace making
- How to assess the Six Factors in your own workplace
The Science Linking the Workplace to User Experience and Performance, Part 1
What should organizations focus on to improve their knowledge workers’ performance? A global research review has uncovered six key factors that have the highest statistical association with the performance of teams: social cohesion, perceived supervisory support, information sharing, vision and goal clarity, external outreach, and trust. These findings give organizations the opportunity to align their underlying culture, value structures, management behaviors, and infrastructure to support these factors.
A single productivity metric for knowledge work remains elusive.
It’s fair to say that everyone associated with creating an organization's workplace – including workplace strategists, planners, designers, real estate executives, facilities managers, furniture manufacturers, and the organization itself – would love to have a single universal, broadly applicable metric to measure knowledge worker performance. If we could easily, consistently measure productivity, we could prove that our recommendations – from the ideal panel heights and the perfectly right-sized workstation, to the right level of ambient noise – have a positive effect on performance (or not). We would have clear decision-making criteria to influence workplace investments and prove results, instead of relying on subjective opinions.
Knowledge work is so varied and its outputs often so intangible that it is not possible to come up with a single universal measure. More complex knowledge work seldom has one single correct or standard outcome, nor are those outcomes usually quantifiable or comparable. In addition, the value of those more complex forms of knowledge work is often determined by the customer demand for it.
In lieu of a single proven metric, many organizations use subjective measures like self-reported job satisfaction, customer satisfaction, or self-rated creativity. Alternatively, organizations may use more objective measures, like absenteeism, employee turnover, number of patents, or successfully completed projects; however, there is widespread academic agreement that these methods are generally not effective as proxy measures, as they are not scientifically valid or reliable.
That said, organizations can develop situationally-relevant productivity metrics for specific types of knowledge work within a specific organizational context. For example, team of product developers may have goals for a particular product, like shortening their usual cycle time or a target sales volume in the first six months after launch.
Answering the question of a universal metric, once and for all.
So, what is known about effectively measuring knowledge worker productivity? To answer this question, Allsteel teamed up with eight organizations across knowledge sectors, including banking, energy, and telecommunications, to sponsor a research project conducted by Advanced Workplace Associates (AWA) and the Center for Evidence-Based Management (CEBMa).
The research team initially set out to find evidence, once and for all, of a single universal productivity metric for knowledge work. CEBMa conducted a rapid evidence assessment, combing through scholarly, peer-reviewed research published between 1990 and 2013. They extensively searched all major academic databases against a carefully defined set of criteria designed to ensure that only the best quality evidence was included in their study, disqualifying any research that represented merely collective opinions or the latest workplace fad. Given the challenges of measuring knowledge worker productivity, the initial outcome of the research is not terribly surprising: a single universal metric doesn't exist.
But the finding led the research team to a second question: Which of the factors that are related to the productivity of knowledge workers are most widely studied and what is known of their effect? Researching this question uncovered six scientifically proven, universally applicable factors that reliably correlate with high performing knowledge work teams. These Six Factors finally give the workplace community academically rigorous evidence on the topic of knowledge work productivity, as well as reliable proxy measures for performance.
The Six Factors summarize 109 single studies and 52 meta-analyses, culled from over 800 research papers. This represents the best available findings on the topic.
The following Six Factors have the highest statistical correlation to the performance of teams involved in knowledge work:
- Social cohesion
- Perceived supervisory support
- Information sharing
- Vision and goal clarity
- External outreach
- Trust
Knowledge work is a team sport
The strongest correlations uncovered in the research are related to the performance of teams. Most of the studies conclude that knowledge worker productivity should be assessed on the team level, because:
- Knowledge work is not an individual task, but it is usually performed in collaboration with others on complex tasks, which individuals cannot perform alone
- Team productivity is not simply the sum of individual productivity
- Changes in productivity of an individual knowledge worker may not affect the productivity
- of other knowledge workers
- The overall productivity of the organization is dependent on the contribution that specific organizational levels (departments, business units, divisions) make towards overall organizational goals
The Six Factors are described in the full whitepaper below in the order of the strength of the correlation to team performance, beginning with the strongest: social cohesion.
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Check out the full whitepaper.