Posted by Kalle Kilpi
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Digitization means changing an analogue process to a digital format. Digitialization, on the other hand, means a game-changing new way of working - a disruption of sorts - enabled by technology.
It’s easy to understand how digitalization disrupts industries like retail shops in a game-changing way. The store is replaced by a virtual catalogue, orders are placed online, customers around the world can access the store, costs are saved, store clerk jobs are made redundant and so on.
It’s harder to understand how digitalization provides a game-changing disruption to knowledge work, such as mergers and acquisitions (M&A). Sure, many meetings are replaced by collaborative tools and Excel spreadsheets are replaced with online project management trackers, but that is not yet real, game-changing disruption enabled by digitalization.
“Online collaboration tools replacing Excel spreadsheets with online trackers is not yet a real, game-changing disruption enabled by digitalization.”
There is no Widespread ERP of M&A / Knowledge Work, Yet
If we look at the above porter value chain, we have already advanced technology to digitalize key work processes around logistics, sales/order entry and customer service, but are very early at digitalizing the knowledge work that develops and supports the core business; processes like corporate development / M&A, legal processes and corporate initiatives.
There is no ERP or operating system of knowledge work. Sure, there are generic tools like the Office suite, contract databases, document management or HR databases, but the actual processes are not digitalized. Every case that lands on a lawyer’s desk, for example, is executed still with generic tools like the Office suite and likely one of the basic database products mentioned above. The process, in this case, resides in the lawyer's mind.
Let’s Break Down Knowledge Work
To understand how digitalization can disrupt knowledge work to the same extent it disrupts brick & mortar stores, we have to dig a bit deeper. Let’s think about how knowledge work, like M&A, is done. You typically have well educated, highly skilled people applying their knowledge to reach outcomes desired by the corporation they work for.
Think about it. Currently, business courses and the associated literature teach us a somewhat uniform view of best practices to carry out processes, and then at companies, we communicate to understand our goals, intent and desired approach in approximately the same way. The consensus is encoded into “tacit knowledge” - a set of unwritten norms, habits, processes and past learning. A highly skilled individual is someone who knows these. The encoding is somewhat vague and even the same person may have a slightly different interpretation every other day.
Tacit Knowledge Must be Encoded in Digital Playbooks
For knowledge work to be digitalized, tacit knowledge must be encoded into digital playbooks that divide the process in phases with clear tasks, deliverables, KPIs and documented best practices for each step.
“For knowledge work to be digitalized, tacit knowledge must be encoded into digital playbooks.”
I’m not talking about business process management (BPM) here. BPM tries to model everything as a flow chart and while that might work for simple things like invoice approval, you can’t really model knowledge work like M&A into an all-encompassing flowchart. We have to have “soft” process modeling. Keep human judgment and intelligent decision making in the loop.
The format must turn the process encoding into “a living document,” where case-specific versions can be created, responsibilities assigned to people easily and the knowledge served in digestible pieces. This living document far outperforms and outlives a static guide-on-the side process, which likely requires extra reporting on top of your having to do the actual work in a separate place from where the guidance is provided.
The format must be such that it is easy to assign parts of the process to individuals (or machine A.I.), it is easy to flex the process to individual situations, track progress of what's been done and develop the process based on learning.
A Revolutionary Change
Companies will have clear “playbooks” for how to analyze acquisition opportunities, handle litigation and run six sigma projects. This is: 1) the best known way to do so and, more importantly, 2) the most effectient way, as almost anyone can follow a project step-by-step to execute it well.
Suddenly, far less experienced and less skilled employees can execute demanding tasks without much hand holding; an immediate productivity boost for them. For the high-level managers, who develop the ways of working, this enables them to put their organizations on “auto-pilot” and assign people (internal or external) to tasks with confidence without having middle management. Without the bottle-neck of having to find skilled workers, hundreds or thousands of initiatives are then able to run in parallel.
Thanks to the easy assignability of tasks, you can negotiate thousands of contracts, integrate thousands of acquired dental clinics or run thousands of six sigma projects in parallel.
You can also build mechanisms for continuous improvement by making adjustments as you learn from every case. This starts to create internal network effects. The more volume you have in a process, the better it gets. It becomes a self-reinforcing competitive advantage.
The ERP of M&A / Knowledge Work is a Digital Playbook Platform
Without technology, M&A and knowledge work process definition initiatives have systematically failed in becoming actionable and having practical value. Typically, process improvement initiatives produce a long process guide that ends up collecting dust with no one really following the process or having time to improve it based on past learnings.
Technology that disrupts knowledge work processes is technology that makes it easy to define, execute and improve the process in an agile way.
Unlocking a New Dimension of Possibilities: A.I., Gig Economy and Beyond
You can outsource, off-shore or insource work, as you find most convenient. It's possible these practices are necessary to truly launch gig economy in knowledge work. Perhaps a new kind of partial process outsourcing or virtualized departments will emerge.
It becomes much easier to harness A.I. to handle tasks when the process is broken down into phases and tasks with clear interfaces. Combine that with an accumulation of knowledge, mix in some pattern recognition and you can have proactive risk and opportunity recognition.
This will also take data and BI driven process improvement to a new level as you now accumulate data that you can analyze, mine and use for bottle-necking. You can then understand what works, what doesn’t, deploy process improvements easily and scale successful patterns with ease.