POINT-of-WORK:  The Great Convergence of Thought and Action

Point-of-Work Dynamics

“GREAT” things are popping up lately, like the Great Resignation, Great Retirement, and the Great Reshuffle, as two examples. I am not swayed by the hype because these all point to one common denominator – Change…and the need to LEAD it. I believe we see the side-effects surface in the form of a Great Convergence of Thought and Action and forms influencers that directly impact Culture. In other words, resignations, retirements, and reshuffling within and among organizations are driving the need for a strategic re-think and adopting tactical actions that are agile and responsive to the lack of a treasure trove of opportunity…reshaping, upskilling, and reskilling to optimize the workforce at the Point-of-Work. Convergence is happening with us…or without us. What is converging in our world of L&D, and how should we manage it? How does it impact Culture?

If you follow my blog, the concept of Point-of-Work Assessment (PWA) has been the subject of many posts and carries a critical linkage to the concepts of convergence. I say “concepts” in the plural because several variables are directly impacting the impact of convergence or as a collateral by-product of convergence. Therefore, the opportunity for Learning & Development (L&D) has multiple influencers to consider, not the least of which is embracing a strategic re-think. As a result, new innovative solution potentials present as many challenges as viable solutions. This short post will hopefully plant some seeds of thought around a critical question – What are the faces of convergence, and what do they produce as opportunities to think and act differently?

Since retirement, I’ve stopped Point-of-Work Assessment Workshops at $595 per person and converted the entire workshop and worksheets to a book “Confessions of a Performance Ninja: Optimization of Workforce Performance @ Point-of-Work.” The book is designed to be a field guide at a fraction of the cost and elimination of listening to me for three days. Bonus!

Learning Culture of Change

An organization’s culture will face a shift as a product of convergence when emphasis requires embracing innovations that impact workflows and often accompany the integration of digital technology. Digital Transformation comes to mind…and unfortunately…with the not-so-good news that upwards of 80% fail. Technology does not fail…we fail. We fail to accomplish leading transformational change effectively. We fall short because we stop short. Unfortunately, we seem to have mastered only the first of four traditional phases of Transformational Change:

  • Deployment – We deploy new training. IT deploys new technology. We train for GoLive, cut the ribbon, and move on to the next training project. What we seem to fail at regularly is the second phase…
  • Implementation – Implementation happens at a new ground zero of Point-of-Work. That is why assessing the Point-of-Work is less deployment and event-focused and more post-GoLive implementation and Change insurance-focused. And if we fail to implement, we fail to reach a critical mass that compromises reaching the third phase…
  • Adoption – Adoption represents that time and place where solution utilization is accepted as best practice and regularly and effectively applied by the user population. The final phase is often overlooked as well…
  • Sustainability – Have protocols been established and integrated to ensure Change Adoption is not just a temporary flash in the pan? Have we created flexibility and resilience in the Process of Change to endure the dynamics of Change? Are we equipped to keep the Change alive and agile enough to respond to ongoing business fluctuations?

Precede the traditional four phases with the fifth – DISCOVERY, also known as Point-of-Work Assessment. I submit DISCOVERY is a significant phase that should always precede Deployment. We must complete due diligence to respond to requests of realities often different throughout the leadership cascade as we head down to the workforce’s Points-of-Work. This knowledge is essential for successful Transformational Change.

  • Discovery – We too often default to responding to requests without performing due diligence as to what prompted those requests. We should accomplish due diligence specific to answering several pivotal questions:
    • What needs to be achieved?
    • Why does it need to be achieved? What is a driving business need?
    • Who engages at all levels to ensure achievement?
    • What is the current state of leadership readiness…workforce readiness…technology readiness…validation readiness…monitoring readiness?
    • What measurable results do we need to validate and monitor achievement?
    • And most importantly…What are the underlying root cause factors preventing Change from being achieved?

Again, I suggest the addition of a fifth phase to Transformational Change – Discovery. We must look beyond requests for pursuing Change that are often based on assumptions and hypotheses despite them being well-intended and uncover root causes behind the motivations that drive the demand for Change. Prioritization should then follow to ensure we start small and scale. Omitting these steps of Discovery can spell failure to optimize something as complex as Digital Transformation and are at the core of Transformational Change Leadership.

Do these phases impact culture? They do because we cannot launch into an extended journey like Digital Transformation as a series of deployments left to flounder after Deployment and neglect the momentum to gain critical mass and strategic thinking to include all subsequent phases of Change. I used Digital Transformation as an example; however, any size project should experience all five phases of Change for consistent expectations and process workflows.

Is this convergence? It is by a strategic re-think keyed on workforce performance converging with the tactical demands of optimizing workflows throughout all five phases of Change. Embracing a repeatable Change model sets organizational expectations and supports consistent best practice application of Change regardless of size and complexity.

Workflow Learning

Thanks to the pioneering work by Bob Mosher and Conrad Gottfredson of APPLY Synergies and their well-known Five Moments of Need, we see a growing acceptance of Workflow Learning. This is a dynamic real-time convergence of learning with work; in fact, the convergence of learning and support within live workflows is enabled by leveraging agile design methodology and delivered via digital adoption platform technology solutions. Workflow Learning exemplifies leading Transformational Change because all five phases of Change are addressed from initial Discovery to complete our due diligence – to Deployment of learning and support solutions – to Implementing directly into workflows at Points-of-Work at specific moments of need – to full Adoption via supporting and refining best practice performance – to Sustainability via protocols designed to maintain and adapt agile solution content responsive to changing business conditions.

Artificial Intelligence (AI) Integration

Recently, the buzz around AI has frequently been surfacing. To many, AI is a mystery, but it comes into better focus when considering specific applications that can be used and controlled. Augmentir has done groundbreaking work in the manufacturing sector with Purpose-Built AI in conjunction with performance pattern recognition within connected worker performance data at Points-of-Work yielding actionable analytics to enable targeted learning to upskill, reskill, and performance support solutions in the workflow.

The targeting is not limited to workflows and processes, but through the added power of AI, data points can be captured within workflows at the step level AND by individual workers. The level of granularity can produce more data points than humanly possible to analyze and too much data to easily extract patterns that can optimize performance and enable effective upskilling and reskilling within workflows specific to identified workers. This is a convergence of data analytics and purpose-built AI technology.

AI-driven data convergence enables another collateral convergence of informed learning and support design from the multi-datapoint granularity of worker performance results at Point-of-Work. What L&D team would not want to know who needs help…when and where in the workflow they need it…visibility to investigate why they need it…and what the solution or refinement should be?

Closing Thoughts

This is an exciting time to be in the L&D discipline. The call to action has become a business imperative of the many faces of convergence, the most prominent being the urgent demand to be responsive to business risk converging with the demand for optimizing agile, measurable, and sustainable workforce performance at the Point-of-Works. This business convergence is driving the need for performance consulting disciplines to converge with the operational stakeholder population with the capability to Assess Performance at Point-of-Work and serve as liaison (still more convergence) with L&D design, development, and delivery capabilities as well as with other functional resources like HR-OD, Process Improvement disciplines like Lean Six Sigma, and IT technology resources.

Please let me know what your thoughts are. Always open to chatting and digging deeper if the need arises.

Take good care!

Gary Wise

Workforce Performance Advocate, Coach, Speaker
(317) 437-2555
Web: Living In Learning