Our thinking: Successful digital transformation

For nearly the last three decades, enterprise resource planning (ERP) systems have been at the center of most enterprise technology strategies and architectures. That model is changing rapidly.

Cloud is an essential component of digital transformation. Moving an on-prem system such as an ERP solution to the cloud will deliver significant advantages.

Accessed via standard web browsers from anywhere with an internet connection, cloud-based solutions are often easier to use and require less training and support. Security, scalability and availability are all but assured. Software updates including enhancements and powerful new features come automatically and at a much faster pace — every couple of months (or faster) instead of every three-to-five years — and so the gap between on-prem software and its cloud alternative widens by the day.

While those are compelling advantages, that is not all. You will also gain agility, flexibility and data-driven insights if you embrace the cloud model fully.

That model includes new "cloud native" methods and technologies such as microservices that are designed to take full advantage of the distributed nature of the cloud. Using these technologies, makes creating, deploying, updating and scaling cloud applications (and their business capabilities) far faster and cheaper than traditional software development methods.

Nevertheless, cloud isn’t a technology model as much as it is a business model. Embracing the cloud can involve new products, new markets, new talent, new operating models, and even entirely new business strategies.

Selecting the right combination of cloud solutions, and customizing and integrating those solutions for your specific needs is both a significant technical and business challenge, independent of the larger organizational and strategic changes that will be required. You must deftly navigate this if you hope to realize the cloud’s full value.

While there are many reasons for fully embracing cloud, cost savings is no longer one of them, despite its initial promotion as a cost save.

It’s true that compared to maintaining your own data center, the economies of scale and shared resources model that the cloud offers along with the shift from capital expenditures to operating expenses, did indeed create efficiencies and financial advantages. But many have found that their journey to the cloud is an order of magnitude more expensive than they had hoped.

The efficiencies and financial advantages haven’t gone away, but much of the savings will be consumed by the cost of new advanced capabilities. If you also factor in the cost of all the non-technology components involved in a digital transformation, such as hiring new talent and organizational change management, any savings may be paltry.

But even though moving to the cloud won’t save money, it’s still worthwhile. The alternative is an on-premise infrastructure that is falling behind faster than ever. Make the investment.

From artificial intelligence (AI) to low-code and blockchain, the expertise required to develop and manage today’s modern technologies may be well beyond the immediate reach of your team – at least in the short run.

Perhaps a good analogy is the disappearance of amateur DIY auto mechanics — the skills, tools and technologies required to fix today’s high-tech cars have simply outpaced what most weekend warriors could handle. You have to know when to turn it over to the professionals, and when it comes to modern technologies, the major cloud players are light years ahead of where you likely are. You don’t want to be struggling to maintain your Model T while they’re cranking out Teslas.

Leveraging third-party expertise offers many advantages while you build and train your team. Clients often bring in my team for this very reason.

AI and other machine learning technologies are essential for deriving insights from your data. But there’s a common misperception that AI can do it all by itself. AI is designed to replace people, right? Perhaps someday, but not yet.

While AI is remarkably good at detecting patterns in massive amounts of data that humans might overlook, it’s still very poor at ascribing meaning without the proper industry and functional context or cues. It lacks creativity and the ability to innovate. It can’t build or train its own models. It can’t decide on what data it should include or exclude. It can’t provide its own governance. At least for the foreseeable future, AI functions such as data cleanliness, model design, training and retraining, will all require significant human involvement. AI is a powerful new tool, but it’s just that: a tool. Like the computers that appeared on our desks in the late 1980s, AI can enhance what we do and even open the door to entirely new business models, but it’s only valuable in the hands of people who know how and why to use it.

Make sure you invest in the right talent to manage your AI apps.

All too many organizations have tried to make one big leap to the cloud and, after spending tens of millions of dollars, wonder why they did. But moving to the cloud doesn’t require you to jump into the pool headfirst. You can start by incremental adoption.

It’s important to invest in things that will deliver short-term return as well as others that offer long-term benefit where the return may not be as assured. A balanced portfolio approach will help limit risk and accelerate benefit.

As a board member, you need to embrace long-term moves, but if you don’t see them tied to business benefit in the short and medium term as well, you should proceed with caution.

In the end, boards need to understand that technology should not be considered in a vacuum. Technology decisions only make sense within a larger digital transformation strategy, which is why clients often approach organizations like us rather than simply hiring technology vendors.

The choices you make for technology investment must reflect your business priorities. Understanding these five things will help you get it right.