I just finished reading The Decoded Company: Know Your Talent Better Than You Know Your Customers,1 which explores several different balls in a complex, intersecting Venn diagram of current businesses and attempts to describe a new paradigm for organizations, particularly for firms relying on innovation as their key competitive strategy. Since innovation is still a unique human endeavor, the authors focus on people, particularly innovators. The book goes into detail about how to recruit, retain, utilize, and manage trophy intellectual talent. Case history summaries illustrate the points.
The authors are very critical of the yearly performance review. These are too infrequent and angst-filled to be useful in modifying behavior. Even if the review is very favorable, the “upper” quickly fades. In place of the review, they recommend weekly, short (<20 minutes) scheduled review meetings between the manager and each subordinate. Topics include: What did you do since the last meeting? What do you plan to do next? What can we do to make things better?
The manager also has some perks that he/she can bestow almost impulsively when the situation warrants, and the manager is motivated to be generous in using the perks. Find something going right, and reward it, now! Frequency and spontaneity are important.
However, other descriptions are often so abstract that I had difficulty seeing how to reduce them to practice. I frequently thought of how this would work in a drug development or QC situation, where the work is locked down with regulatory and legal enforcement. My conclusion is that this is not a fit.
The authors make the point that new technology; particularly big data analytics, enables a change in workflow and organizational structure. Data drive decisions replacing gut-feel or experience. People have been measuring and optimizing work for decades. Recall the post-WWII efficiency experts with their clipboards and stopwatches. These studies broke divided production work into individual steps. These were characterized by time, cost, safety, etc. Output was then benchmarked to other scenarios. The individual was standardized, leading to depersonalization of the work, the job, and the worker. Assembly lines relied upon the interchange ability of workers, further separating the worker from identifying with the product.
There is a danger that with big data, this process could accelerate. With digital devices, it is even easier to curate and process huge amounts of data. The authors point out that with a little care and human sensitivity, the data can be used to personalize the work experience, leading to motivated, highly productive teams doing satisfying work.
My impression is that the authors have a good point that big data does not necessarily lead to an Orwellian big brother model. The data could also be mined and used in a benevolent way, if the organization’s leadership has the skills and confidence to manage them.
1. Segal, L.; Goldstein, A. et al. The Decoded Company: Know Your Talent Better Than You Know Your Customers. Portfolio/ Penguin, 2014. ISBN 978-1-59184- 714-4.
Robert L. Stevenson is Editor, American Laboratory/Labcompare; e-mail: firstname.lastname@example.org.