Digital Transformation: Lessons Learned From the Trenches

It’s been over 5 or 6 years since the term “Digital Transformation” was coined as the strategic initiative that would lead companies, governments and not-for-profit organizations into the new world of work that we sometimes call  the Industry 4.0.

From digital printing and the “Internet of things”, to analytics, robotics and artificial intelligence, almost every person in the planet is being bombarded with a rate of change not seen in many years and we think will transform Society as the industrialization did 150 years ago.

So, after almost a decade or more of high connectivity and around 5-6 years of full-engagement by many multinationals in their digital transformation initiatives with few restrictions on the resources needed to pull them out – or so they thought – what have we learned?

2019 has been a year of reflection when it comes to Digital Transformation. Many of the IT and business leaders are looking back and evaluating this decade of “digitization.” If you google “Digital Transformation Fail” you will find a plethora of articles, interviews and news from every source possible, with one thing in common: the reflection on what have we learned and how to apply it looking forward.

Transforming Digitally: What have we learned and how do we move forward?

We now know that the failure rate for digital transformation initiatives is deemed to be high (as ERP implementations were 20 or 30 years ago) but, what are we calling a failure? Well, failing to transform. Many companies have invested a lot of money and resources into this new “Holy Grail”, and have been successful at completing those projects. They may even have a sizeable project portfolio on their pedigree.

But are they transforming?

Are they realizing their full potential and reaching the promise they started with? It appears that only a few feel that way.

We know now that failing to realize full potential rarely has to do with the technology or automation, per se. Those digital pioneers have found that the change management for RPA, AI and even for analytics is more complex than was needed for ERPs, and that achieving a true “Digital Mindset or Mentality” has been very elusive.

Among the root causes of this “failing to transform” symptom are:

• Insufficient Scalability: many organizations start with pilots, get excited and start doing robotics or AI all over the organization, but sometimes the choices made along the journey or the lack of a strategy to implement gets them into a fragmented scenario where they seem to have trouble to get out of prototyping and pilot projects.
• Excessive cost or insufficient benefits: if you don’t scale or if you do it in a costly manner, the TCO (total cost of ownership) of your digital initiatives could find hard to justify when measured against the tangible – EBIT tested – results.
• Lack of focus: At the end, if you don’t focus, you may have projects all over the place and not necessarily in line with the same technology, leveraging your investments and even being pointed to the same objectives. Lack of focus brings sometimes lack of governance. Be sure to avoid a plethora of “maverick projects” with no conceptual spinal column.
• Technology for the sake of technology: Not every process or task is worth to automate. Many factors need to be taken into consideration to choose where to invest your automation resources.
• Lack of “Digital Culture” or issues with change management or communications within the organization with respect to Robotics, AI and other technologies: Unfortunately, most of what you read in the newspaper about robotics las a negative view, so employees need to understand not only the potential negative effects but also the potential benefits of having a digital workforce. Companies need to take control of the narrative to employees to help balance their views and expectations.
• Misalignment between the general and business strategy and the RPA or AI initiative: I’ve written before about having strategy first, for example, about the need to put the Customer Journey as guiding light when automating the “Order to Cash” cycle.

For these reason, the lessons learned point towards having a “Non-technology” work stream along the automation initiative, that help the organization steer the course in the direction of strategy, take control of the narrative to the organization and ultimately, influence the organizational culture so that the organization actually “transforms digitally.” One employee at a time.

I propose that the best way to do that is to have a dual approach, where the managing consulting part of the equation (the Strategy and Operations consulting) works along the IT Execution Consulting in implementing the solution.

IT Execution Consultants often handle one or more technologies (the platform component), so they help the client (the Organization’s IT function) be effective and efficient towards implementing RPA, AI or any other technology. This is a great value to the organization. But the Management Consultant should be separate – working along the tech consultants but having their alignment and priorities directly with the Client.

This also, by the way, is a good practice in terms of consulting ethics and avoidance of conflicts of interest. A professional management consultant must keep his/her advice independent in order to better serve the client. International standards organizations for management consultants such as CMC-Global enforce these guidelines when certifying a Management Consultant. Also, the standard from ISO (the International Standards Organization) about how to conduct professionally a consulting engagement, ISO20700:2017 enforces these clear definitions and separations as well.

In the approach we suggest our clients, the same initiative has at least 2 separate components, but with a common goal and deliverable: a Strategy and Operations consulting segment that overlaps with the Automation and IT Execution Consulting, both looking at the end results but from different perspectives.

They overlap in the process improvement area, since process cycles (OTC, Procurement, RTR or PTP for example) need to be strategically oriented, but the detail of how to perform those processes digitally and the possibilities to scale depend on the technology used. This is where both segments agree on “ the what” and “ the how” the Digital Transformation should be done.

If you are already into the Digital Transformation bandwagon or if you are just entering the RPA or AI space for your organization, make sure you have an approach that keeps you grounded in your strategy, your business model and what you produce that is of value to your customers or clients.