5 hot digital transformation trends — and 2 going cold

This is not something people need to learn; employees have figured out how they work best, he says.

Future work is focused on what people are doing and how they’re providing value, whereas hybrid work is about how do we continue operating when people won’t be in the office 100% of time, adds Sacolick. Yet, “what’s interesting is over 60% of companies in the tech space remain hybrid.”

In other words, if you haven’t figured out how to make hybrid work by now, you’re still likely not ramping up solutions to address it. In fact, enhancing hybrid work technologies was the No. 1 decreasing priority for IT leaders, according to the State of the CIO survey, and many CIOs have long been unraveling the ‘pandemic debt’ incurred by investing in digital productivity solutions during the height of the pandemic.

Hot: Digital trailblazers and micro transformations

With the CIO role changing to be more business-oriented and focused on both internal and external customer needs, CIOs need more of what Sacolick calls “digital trailblazers” who can act as “lieutenants.” These are people who “understand the lane they’re working in, whether it’s apps or security.” It’s incumbent upon CIOs to groom them to become leaders with “outside-in learning,’’ through a combination of attending nontechnical industry events and finding mentors outside the organization.

The trailblazers should be branched out into the business to run smaller transformation programs, he says.

Dean Kontul, executive vice president and CIO of KeyBank, is also a proponent of implementing micro transformations alongside large-scale transformations. 

The bank uses a pilot test-and-learn approach wherever possible. Along these lines, KeyBank uses consulting and outsourcing partners to accelerate the process. 

“Our most successful transformations rely on leadership across KeyBank and on speed of delivery with multiple impactful components delivered in parallel, versus waiting on a big-bang approach delivered all at once,” Kontul says.

This may not be bleeding edge, he notes, “but we certainly are forward-thinking and adopt new tools quickly and proactivity look to apply lessons learned from small initiatives with emerging technologies to broader use cases.”

Instead of the conversation being about a big, monolithic ERP transformation, CIOs should think about agility, Schneider Electric’s Cain says. “Do you think agile or are you agile? Look at [digital transformation] on a micro-scale and transform the way you work with a modular approach.”

Hot: Business-IT partnerships

Similar to Dow, Schneider’s IT group has been structured to be aligned with specific business domains “to better enable the business and be a better business partner.”

Not everything has to be enabled by technology, Cain adds. “You don’t want to just automate a crappy process — change the process.” Schneider uses an approach called a “power couple,” which pairs a domain or business leader and a digital leader together. They are responsible for the ‘what’ and ‘why’ and the digital leader is responsible for the ‘how’ and the ‘when.’

“When you partner those two people together … it’s very, very powerful and you don’t burn a lot of calories in solutioning and trying to do other people’s jobs and overwhelming people,’’ Cain says. “We utilize [them] in a dual delivery leadership model — the same people, the same rank, the same level and we put them together.”

Hot: Embedding AI in enterprise systems

There was a time when embedding AI and machine learning into enterprise and SaaS platforms fell to data science teams, but now, organizations are expanding those programs, Sacolick says.

“They’re looking to use AI and MI in ways that deliver value … beyond what marketing is saying [these platforms] can do. It’s not about the science but the application and getting the value without having to invest in the skillsets to build the models,” he says.

Take recommendation engines. They have been around for many years inside ecommerce and content management systems, he notes. “The CIO and IT have to make sure the information is presented to [the recommendation engine] in a way so it will make better decisions,’’ Sacolick says. “That often means expanding the context and data available to it.”

Ruga agrees, saying that applying AI or machine learning with “data inputs that make sense” makes large systems more valuable. At Fictiv, IT is doing that for quotes for manufacturing parts.

“Now you have something that has been educated by machine learning that has seen lots and lots of similar examples and can infer the conditions that are necessary to say, ‘This configuration or this design will cost you X dollars to make,’ and makes recommendations,’’ he says. “We are seeing that everywhere.”

Hot: Digitizing the manufacturing supply chain

Digitizing the entire supply chain is at the forefront for BSH, a Munich, Germany-based global provider of home appliances, says Berke Menekli, senior vice president of digital platform services, whose digital strategy tackles four pillars: enterprise processes, manufacturing processes, products, and the consumer journey.

BSH’s approach incorporates Industry 4.0, or I4.0, an IT-fueled strategy for improving efficiency using automation and data-driven operational decision-making.

BSH

To achieve this, BSH is investing in inbound/outbound logistics flow to maintain the continuity of production and supply chain automation “to ensure value creation toward our products can be transferred to our consumers,” Menekli says.

Initiatives such as these have become hot, he says, thanks to the advancement of supporting technologies such as machine learning and data lakes, which have become fast and strong enough to be operationally reliable in a manufacturing environment.

Taking that a step further, Ruga says it’s become more important to insulate the manufacturing supply chain, given global socioeconomic conditions.

“If I’m faced with a scenario like COVID or the war in Ukraine, and I have tons of people I employ and tons of vendors that depend on me and all of a sudden COVID hits, my supply chain collapses,’’ he says. Or “maybe I had a manufacturer in Ukraine that was producing unique parts for me, and … that factory got blown up and now I have to find a new vendor, which costs me time and money.”

A new trend is for manufacturers to vet their networks to insulate their supply chain and have the work managed for them, Ruga says.

“It’s not about whether I put Oracle in, it’s whether the collection of systems I’ve put in place insulate my business from risk,’’ he says. “An outsourced insulated supply chain de-risks things like supply chain disruption when COVID hits and a machine shop shuts down.’’

Cold: Traditional RPA

Some IT leaders are finding that robotic process automation is a lever-based approach involving the time-consuming process of collecting financial and operational data, and detailed process mapping, and doesn’t have enterprise scale. Many of the initial bots developed focused heavily on process efficiency, and this has limited opportunities for scalability, observers say.

Organizations must rethink how work is being done with bots that are broader in scope, or the investment in them will underdeliver.

Sacolick thinks RPA has become a band-aid. “I think what we’re doing is scripting on top of broken processes, in some cases, data technologies, and in many cases, a lack of APIs to get a backdoor into digital capabilities.” This is leading to an accumulation of bot debt because “any time I build a bot I have to continue to evolve and support it.”

He believes organizations will soon be talking about RPA more as a set of integrated tools, or what Sacolick calls hyperautomation, using low code and machine learning.  

“A bot is a piece of a solution, not a complete one,’’ he says. A lot of what they do is fill out forms and ‘screen scraping.’ In invoice processing, for example, you can either outsource the work or build a bot that will do some data entry internally instead of having people key the information into an ERP system.

That saves time and money and avoids mistakes and the need to change vendors, he says. But when a vendor changes their system or the company updates its ERP system, the bots will have to be changed, and that causes the debt, especially when the vendor doesn’t have an API the company can use, Sacolick says.

Another approach is to build a low-code system that flows into the ERP system through an API. “RPA is a tool to orchestrate a workflow, low code is a tool to build a workflow, and machine learning is tool so my workflows can be triggered based on analytics,’’ he explains. “RPA will shift from being a platform to a tool. It’s providing one capability; it’s not that powerful alone.”

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