A recent Article by Accenture “Change What’s Possible for Your Business” reveals a compelling need to transform our approach to generating sustained performance. Their article states “Although 90% of today’s businesses have adopted cloud, only one third are achieving the anticipated ROI. The most advanced companies understand that while cloud sets you up with next-level computing power and access to new kinds of data in the right quantity and quality, AI is the bridge to convert that data into business value.” Accenture refers to this value add as Applied Intelligence and further posture “that cloud is the enabler, data is the driver, and AI is the differentiator.”  

For so many years my focus has been on bringing Performance Support (PS) into the workflow using Electronic Performance Support (EPS) technology and enhancing training with the same technology. I now see an evolution that is a step-change beyond basic PS and job aids accessible at the moment of need. There is another aspect that data reveals that we cannot overlook…the efficiency of task-level execution. In other words, the Connected Worker’s actual connection is greater than completing task successfully; in fact, it is two-way.

That said, I see two recipients to the value extracted by integrating AI into a potential tsunami of data. The first is the Connected Worker…the second is the organization tasked to optimize the performance of the Connected Worker. To me this means data is only of actionable value if extracted and translated into meaningful data-driven analytics.

There are questions that present themselves that we rarely consider and are data points we do not routinely extract to a usable degree:

• How efficiently was the task completed?
• How many failed attempts were made to complete the task?
• What were the sources/causes of those failures?
• Were performance support objects effectively designed and efficiently applicable?
• What other information/resources were used to complete the task?
• What user technology and technology platforms were engaged in task completion?
• How effectively and efficiently did the Connected Worker interface with those technologies?
• Were those support and resources seamlessly, frictionlessly and ubiquitously accessible at the moment of need?
• Does the technology exist that enables optimized accessibility?
• How much did a completed task cost?
• Are there other Connected Workers contributing similar costs when completing the same task?
• What actions or inactions caused cost to be higher for some and less for others?
• Based on the analytics, what tactics to improve/change/integrate new training, support, resources, and/or technology are planned or under consideration?
• What other analytics are possible and necessary to optimize the dynamic nature of your learning performance ecosystem?

My background as a performance consultant embedded with learning and performance support disciplines, always returns to the significance of Point-of-Work because that’s where task-centric and role-specific business results and performance data are generated…in the worker’s head and heart…in the user technology utilized…in the resources and support available…in the performance data regarding success, compromised results, and/or outright failure. As a leader, I would be hard-pressed to make informed decisions without answers to the brief list of questions like those above.

To this camper, it is clear the data flow from the Point-of-Work to Informed Insights critical to drive effective Decision Making must be two-way. Obviously, we need data from actual execution activities to track Point-of-Work effectiveness, but there is something else we need to inform and optimize – Workforce Engagement.

Engagement of the workforce needs to yield a sense of job satisfaction validated through visibility of personal results and performance contribution. Engagement heads off the attraction of the Great Resignation. Engagement enabled early in reduced onboarding time and rapid speed to effectiveness in assigned tasks reduces stress and frustration of learning a new job. Learning task-centric and role-specific requirements IN the workflow seamlessly with no friction and available 24/7 wherever the Connected Worker is in their workflow is essential. Receiving prescriptive development based on individual performance versus one-size-fits-all training shows the organization is engaged in my success.

Every worker wants to be successful and building a culture of enabled performance can only help. It is in the data…when the data is transformed into data-driven analytics to inform sustainable change and optimization.

Gary G. Wise
Workforce Performance Advocate, Coach, Speaker
gdogwise@gmail.com 
(317) 437-2555
Web: Living In Learning
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