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Digital transformation: Not so difficult with the right strategy

Dec. 19, 2019
The biggest problem with most digital-transformation initiatives is a lack of priority.

By AJ Naddell, principle product manager within IBM’s Watson IoT division

Buzzword alert!

What do all of these terms have in common beyond being alphabet soup?

AI, IoT, blockchain, machine learning, cloud, hybrid multicloud, quantum, RPA

IBM's AJ Naddell

They are all a part of digital transformation.

Digital transformation—or digital re-invention—are THE big buzzwords. They are top-of-mind for every chief executive. And yet, I often hear “It’s a complex process and too expensive. I don’t even know where to begin.”

This should not be the case…with the right strategy.

The biggest problem with most digital-transformation initiatives is a lack of priority, direction and senior-executive support. The initial focus should be on use cases that will drive the quickest payback and highest ROI. This sounds obvious, but most companies find this evaluation very difficult.

I suggest that clients start by determining a critical area for their business that will drive a significant portion of business risk; this approach allows them to start with a small investment that will have the potential for funding the entire transformation. 

Ultimately, the main outcome of digital transformation is to help your company win in a competitive market; starting with the most critical areas enables just that.

So, the next questions: Where do I get started? What is the project that will kickstart my self-funding transformation?

I believe the answers to be quite simple: as mentioned above, companies should start with the operational assets that drive the greatest business impact and expose operations to the most-significant risk. In my field (asset-intensive industries such as energy & utilities, oil & gas, industrial manufacturing, travel & transportation) this means focusing on assets that drive the vast majority of revenue while also bearing the brunt of operations costs.

For most companies I engage with, this transformation begins with what I call the Journey to Predictive Analytics. While this journey is unique to each company, the pathway ALWAYS follows key milestones:

Manage—Enterprise asset management to manage, set and execute maintenance strategies.

Monitor—Visualize your assets in near real time with OT/operations data at scale, leveraging AI-based anomaly models to drive with both meaningful and actionable alerts.

Health—Evaluate the health of your assets, highlighting problem assets, and plan to repair or replace the asset with the data from the Manage and Monitor stages.

Predict—Predict the failure of your assets and contributors of failure by leveraging both OT and IT data from all of the above.

Although each of these stages are common across customers and industries, the unique part for each customer is determining the starting point, which is wholly dependent on each customer’s maturity. (This holds true for all phases of the broader digital transformation.)

Coming back to a financial POV, each of these milestones provides unique and additive value. Examples:

  • Decreasing unplanned downtime 80% by predicting failures several weeks in advance
  • Optimizing operations activities
  • Creating new business models through after-sales support with recurring revenue
  • Providing end-to-end visibility for senior executives into company operations for planning purposes

There are myriad opportunities to create significant value for shareholders while substantially decreasing financial risk.

Based on my experience with customers, the combination of these milestones can easily provide payback within 3-4 months, with more than 400% ROI over three years, generating $10Ms in annual benefits for companies, which can fund scaled-out transformations.

But remember this: getting started now is critical. The longer you wait, the greater the chance of being disrupted. Once you fall behind, it is very difficult to make a comeback.