A cheat sheet for the workplace jigsaw
Our new long form (and free) report encompasses Process Mining, Task Mining, RPA, BPM, Workflow Automation, Decision Intelligence, Process Orchestration, Low Code and No Code platforms. As from a buyers, and users perspective, these technologies are all used to automate and monitor business process activities. In the report, we provide a framework that can help vendors and buyers alike to create value and we identify where technical and commercial partnership opportunities may lie. In fact, we go quite a bit further and essentially reframe these existing and typically siloed technologies under a single, self-supporting and, we hope, logical and practical framework.
Currently in production for release at the end of Q1 2023, we will be publishing a detailed market dynamics and market sizing analysis for the period 2023-2028, providing further insight into the Work Intelligence marketplace.
If we were to see attempts to understand our workplaces as akin to trying to solve a massive jigsaw, then this decade has seen the pieces swept back into the box and shaken up on multiple occasions. The most recent of these events – employee decimation by many of the largest companies in the tech industry – is still unfolding, and it’s hard for us not to feel the personal effects of that right now as we scroll through the traces of the human impacts of those events on our social media streams.
When Deep Analysis first started to piece together the parts of what became Work Intelligence, our primary goal was to link together what we saw as parallel, potentially complementary trends within the software markets that we were already tracking. The goal is to help explain how their application could be beneficial to the way we work. Having observed the “Future of Work” cycle within the software industry a decade ago, where the result generally posited was “a better inbox,” we were keen to find something capable of delivering a weightier impact.
Rather than looking at the symptoms of work, what we were interested in was the underlying processes that defined work itself. Where we were seeing a desire for automation, increased use of artificial intelligence and a perceived improvement to organizational efficiency, how did these elements fit with the needs of the employees, the human intelligence with which it was to be intertwined?
Critically, we diverged deliberately from the notion of efficiency.
Poor efficiency is a badly bruised term, primarily because it is often squashed into whatever shape is required to provide a rationale for a decision that has already been made but still requires some form of justification beyond the actuality. For many organizations, that efficiency equals the difference between income and expenditure. The way of achieving that efficiency is often through the decimation mentioned above and the myriad of sad personal stories.
Instead, we focused on organizational health.
Indeed the phrase “An organization’s health can be defined by and diagnosed through an observation of the processes that operate within it.” opens our first Work Intelligence report, “Work Intelligence: Improving Processes by Balancing Human Intelligence and AI” which is available to download today (free of charge for registered users).
Within the report we outline how the practice of Work Intelligence can provide organizations a path towards process analysis, augmentation and improvement, through an equal partnership between human and machine intelligence. Rather than digital transformation, Work Intelligence – cognizant of the realities of the current economic landscape – is instead about digital harmonization. This is apt, as today there is neither the appetite nor budget for big ticket platform purchases, and ambitious digital transformations. Many organizations are instead looking at development budgets of zero, where money needs to be raised from savings made from ongoing maintenance monies, and the elimination of redundant activities and systems. Yet that is something hard to achieve without access to information to inform the relative criticality – or otherwise – of the current ‘as is’ situation.
Across three broad technology clusters – Mining and Processing, Analysis and Simulation and Orchestration and Automation – that exist within the scope of Work Intelligence, we plot short, medium and long term paths that organizations can adopt (starting with technology that is available and deployable today) toward building an operationalized, healthy and situationally aware future.
In 2023, organizations are facing a short term future where they are expected to do more with less. Many have made an active decision that the first “less” they can do without is people, a resource landscape where skilled people were already proving hard to recruit, is in part helping to drive further interest in automation. Some have intimated that they believe that it was those people who were the cause of inefficiencies within their organizations that hastened the hard decisions to let them go. Many of those same organizations have in parallel intimated that their hiring in the first place was initiated by the reaction to a previous, sudden shaking of the jigsaw box several years previously.
The concept of Work Intelligence, as detailed in the report, offers the potential, through continuous, and holistic process management to offset some of these sudden changes in policy direction that can be so disruptive. Understanding the processes and interactions within, where human and machine intelligence is best applied to achieve a desired output whilst balancing human hunches against any suggested changes from artificial intelligence, to where improvements beneficial to all within the organization, can be formulated, simulated and applied.