What do you think about when you hear the words “digital transformation”?
If I ask ChatGPT to define digital transformation it returns a long set of sentences about strategic shifts in culture, business models, process changes, customer centricity and reimagining blah, blah, blah.
Ultimately, I think about digital transformation as investing in technology to replace and reduce human intervention. In that limited definition, digital transformation really isn’t new, which might explain why it’s referred to as version 4.0 when talking Industrial Revolutions.
Figure 1 – Timeline of Industrial Revolutions
If we think about “why?” and follow the seven “why’s” we might start with reasoning like challenging ourselves to do better, freeing ourselves to do more, changing the way things are to change more of the world; but I think the real root, just like the rest of the industrial revolution, is that we do anything for the bottom line.
Starting over… and over… and over
The hard truth about digital transformation is that everyone only values the end of the journey, touting features like AI/ML and system automation. We tend to start the journey with an expensive centralization effort on one application, and maybe develop some statistics in that application and a few workflows, but rarely do we get the system to a point where it generates larger data analysis or generative decisions; and people lose faith.
Figure 2 – Evolution of digital transformation
A big failing is that we tend to focus on the newest specific application products as our saviour and ultimately end up starting over before we get to the end because the value just doesn’t materialize.
Evolution of a software environment to achieve digital transformation requires a bigger visionary view than individual application automation. To achieve the end goal, we need to build value into the beginning so we can justify that next stage.
So, let’s explore some value…
Increasing our efficiency and scalability
Are you part of the teams looking to reduce IT infrastructure costs?
Deploying in the cloud or purchasing cloud software isn’t always about features. Sometimes it just makes sense to pay for a central IT infrastructure instead of upkeep on multiple server banks or individual computers. Scaling our IT infrastructure means we can introduce new employees as easy as shipping them a client laptop and giving them access to the central network.
When you think about the wasted hours doing local installations without even mentioning the requisitions to the local administrator to set up hardware, maintenance of infrastructure records, scheduling and coordinating software operating system updates, configuring software privileges on individual installations… – the time savings in IT overhead really can’t be overstated.
Why would you insist on maintaining separate operating systems for every piece of equipment and every employee when network solutions exist?
Centralizing and securing data
Have you ever lost an external drive? Spent hours coordinating backups and archival?
Centralizing data isn’t just something to do because you really want a universal file structure. Keeping data centralized means only having to care for one location and through one application.
Tools exist today that allow for mixed data to be centrally housed in lakes and indexed later. Additional layers to the warehouse system can secure the file location independent of individual and independent application privileges. This unifies the security of the raw files away from configuring multiple software and trying to match and maintain the security settings across different security options.
Our data is becoming our most valuable resource and centralizing it on one platform means even if an individual application is cracked, the raw and processed data from that application is kept secure and original.
Taking advantage of the speed of innovation
Does it feel like you just finished installing software on the latest operating system and need to start the process again?
When individual applications secure data, we are limited by the lifecycle of the applications themselves and must update the database in order to use the newest version. Because of this, we wait until the software is updated with new features we possibly can’t live without and avoid the upgrade process as much as possible.
If the data is centralized and kept separate from the applications, it means the application itself can be updated without impact to the data security. This can reduce the fear for our data integrity during upgrade activities and reduce the need to update individual servers, individual systems, or do lengthy revalidation efforts.
Considering the next step Cloud computing and digital transformation have different connotations between users and companies, but there is no doubt they can offer valuable return on investment. If you’re looking for a way to justify a new software, think about value add along the journey. Mapping out the pathway in stages and deciding on a platform that gives ROI throughout the journey makes getting to the end make perfect sense.
To learn more take a look at our Digital Transformation whitepaper or Enterprise, Lakes, Clouds, and Artificial Intelligence blog
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