With headquarters in Boston and over 2,700 employees worldwide, Novanta is an $800 million global supplier of laser photonics, precision motion control, and vision technologies. CIO Sarah Betadam, who joined in 2019 as VP of business applications, and then became global CIO in January 2021, is tasked with the strategic direction, leadership, and implementation of the company’s digital transformation, juggling several initiatives simultaneously, many of which surround efforts to become a fully functional data-driven enterprise.

“My team and I are very proud of our transformation that started in 2019,” she says. “When I joined, there was a lot of silo data everywhere throughout the organization, and everyone was doing their own reporting. So in monthly or quarterly combined meetings, there weren’t apples to apples being compared. It was also a lot of churning for the different groups to come up with those data on the weekly, monthly and quarterly basis.”

So from the business side, there was a lot of inefficiency getting data to the point where it was presentable to different audiences, which presented in its own right a big business problem for Betadam. But where to begin?

“We started from a focused business case by partnering with three different groups to showcase how centralization of data can be efficient, helpful, and a good roadmap for the company,” she says. “You have to build trust within stakeholders, and really prove you can help them help themselves. That’s the first level of a cultural shift. It took us about six months to do the proof of concept for three different business units, but it was highly successful. In fact, the ROI was so high, we gained the trust of our executives to invest in a platform to begin centralizing data.”

CIO contributing editor Julia King recently spoke with Betadam about Novanta’s unified shift from its fractured reporting culture to a more efficient data-driven organization. Here are some edited excerpts of that conversation. Watch the full video below for more insights.

On investing in capabilities: We’ve set up something called a BI Center of Excellence where we train and have workshops and seminars on a monthly basis that team members across Novanta can join to learn about how they could leverage data marts or data sources to build their own reporting. So we have a visualization layer where we teach different groups within our organization to learn. It’s evolved from over the past four years from having nothing and siloed data sets of spreadsheets and everyone doing their own thing, to being centralized based on KPIs and the trust in what they receive from the data. They’re learning how to visualize data on their own, so they don’t really need IT other than the data marts in order to build their own dashboards.

On a positive mentality: Transformations aren’t just technology driven, they’re people and process driven. And change doesn’t come easy no matter which organization you’re at. So when you talk about data, there’s a lot of change that can happen from the way people work to how they manage data, and how you report and make decisions based on that data. That’s integral for any business. When you’re making proposals, if the answer is no, don’t be discouraged, go back and try why there was a no. Keep at it because I’ve heard no throughout my career. If you’re a firm believer of something that will have a huge impact in your business, you just have to have the tenacity to go after it, understand it, try to explain it and educate people on it to create momentum. Once you prove that, then the rest is history.          

On BI maturity: When it comes to reporting and analytics or BI, in order to gain the trust of team members, you have to be able to educate as well as let them know that just the data reporting and having access to data from a centralized view doesn’t mean your data is necessarily accurate, because if you don’t input the data correctly, you get garbage in, garbage out. I think part of educating team members, when we’re doing proofs of concept, is about not expecting a miracle. We have a multitude of ERP systems to map as well as data sources. We could do all that mapping and validation with you, but if the underlying data isn’t accurate, it has nothing to do with the mechanism which provides that. It’s the clean-up effort. It’s about being transparent and educating your business in terms of what the expectation of the BI tool can deliver.

On data governance: We have 17 different ERP systems, and Novanta is a very acquisitive company, so it’s an ongoing challenge. But my team is familiar with different backend technologies for the mainstream ERP. Yet if we come across an ERP that’s not necessarily mainstream, they’ll have challenges getting into the back end, and integrating and understanding the relational data to connect it to our central data lake. That’s going to be an ongoing technical risk that we’ll have and we need to overcome that. What we understood in 2019 was when people don’t see what they’re inputting, they often forget different entry variations, like how many ways there are to say, “United States.” But through some key business cases, and now to the entire group, discrepancies from data duplication are visible, as well as the visibility and movement for data governance that’s spun off across Novanta, and the BI platform and reporting. It’s a work in progress. We’re discovering more, but it definitely helps to have the visibility and data governance to clean the data and integrate the data mapping, which helps the BI team to publish data marts.

Business Intelligence, CIO, Digital Transformation, Enterprise Architecture, IT Leadership

Despite the best of intentions, CIOs and their organizations often struggle to deliver business outcomes from digital transformation strategies. According to research firm Gartner, 89% of corporate boards say digital is embedded in all business growth strategies, but only 35% of organizations are on track to achieve digital transformation goals. And while KPMG reports that 72% of CEOs have aggressive digital investment strategies, McKinsey details a harsh reality that 70% of transformations fail.

Stats such as these raise the question: How can CIOs and digital transformation leaders better recognize failure signs and proactively address issues?

My experience leading many digital transformations is that failures stem from a series of derailments, many of which are inadvertent. Even if digital transformation leaders avoid outright failure, these derailments delay initiatives, create avoidable organizational stress, and often yield underwhelming business outcomes.

Five years ago, I shared that the No. 1 reason digital transformations fail is that executives fail to recognize that digital initiatives are bottom-up transformations that require change across the organization. Employees must understand the why behind digital strategies and have incentives to participate in transformation initiatives. CIOs like to say, “Digital transformation is a journey,” but I believe leaders must strive to lead transformation as a core organizational competency

CIOs can’t be involved in every strategic discussion or dive into every initiative’s details, but there are several high-level signs that indicate a digital transformation may be destined to underperform, especially as CIOs add initiatives. In my experience assessing digital transformations, the following five are the most common. 

1. Prioritize too many initiatives without a shared vision

“One of the most common ways to derail digital transformation efforts is ignoring the importance of a clear strategy and defined goals,” says Arturo Garcia, CEO of DNAMIC.

CIOs must communicate strategy and goals when making investment cases and garnering support from the CEO, executives, and the board. As challenging as it is to get to a yes, it’s what comes next that often derails digital transformations at the very start.

CIOs must facilitate a discussion on priorities. Having too many number-one priorities sets unrealistic expectations with business stakeholders and stresses team leaders. Worse is when prioritized initiatives don’t have a documented shared vision, including a definition of the customer, targeted value propositions, and achievable success criteria.

When I survey transformation leaders and their teams, I privately ask each person three questions: What’s your top priority, why is it important, and how many other initiatives are also taking up your time? The risk of derailments increases as I hear inconsistent answers or too many conflicting priorities.

2. Neglect to set collaboration and communication principles

Digital transformations can start with one initiative, defined goals, and a dedicated team. But CIOs are under pressure to accelerate and find digital transformation force multipliers. That means growing the number of leaders and teams that can plan innovations and deliver transformative impacts.   

“Innovation does not happen in isolation: It occurs when organizations encourage and nurture it, often with processes to enable nontraditional ways of thinking, working, and the space to try out ideas in a safe environment,” says Hasmukh Ranjan, CIO of AMD.

Here’s how I spot derailments: Ask initiative leaders to share access to their roadmaps, agile backlogs, collaboration tools, stakeholder communications, and internal documentation. I seek information completeness, communication consistency, and ease-of-use factors. When CIOs struggle to grow beyond one transformation initiative, the root cause is often gaps in collaboration and communication principles.

3. Customize solutions to meet everyone’s requirements

Many organizations use agile methodologies when planning and executing digital transformation and assign multidisciplinary teams to manage releases, sprints, and backlogs. But are product managers developing market- and customer-driven roadmaps and prioritized backlogs? Unfortunately, many digital transformation initiatives succumb to stakeholders dominating priorities with neverending wishlists and poorly defined requirements.

One recent study shows that only 50% follow a product-centric operating model focusing on customer centricity and delivering delightful customer experiences. “Companies that leverage high-quality data, center their enterprise around responsible risk-taking, and organize around products are the most likely to experience profitable growth from their digital transformation journey,” says Anant Adya, EVP of Infosys Cobalt.

Subject matter experts and internal stakeholders should be contributors to priorities and requirements, not decision-makers or backlog dictators. Digital transformations derail when CIOs miss the opportunity to establish and communicate product management responsibilities for creating and evolving market- and customer-driven roadmaps.

4. Underinvest in developing digital trailblazers

In its 2023 State of Digital Transformation report, TEKSystems found that 48% of tech and business decision-makers report needing to revise the nature of their organization’s talent base, and another 34% acknowledge needing new types of talent. “Organizations can derail their digital transformation journey by failing to map out goals, objectives, and tactics prior to launch and not valuing the right mix of IT and business stakeholders in the planning stages,” says Ricardo Madan, senior vice president at TEKSystems.

CIOs invest in skills development, and HR usually offers leadership development programs, but these approaches often don’t address the knowledge and skills needed to lead digital transformation initiatives.

Digital trailblazers, including product managers, program managers, architects, agile delivery managers, and data scientists, need specialized learning programs and coaching to build their confidence in handling transformation responsibilities. Derailments can happen when transformation leaders seize up when negotiating priorities, fail to facilitate decisions on requirements, or struggle when handling conflicts or blow-up moments. Digital trailblazers face many people challenges when guiding employees through a transformation, and CIOs should identify coaches and development programs to prepare their leaders.

5. Drive KPIs and data-driven decisions without a data strategy

Building digital products, improving customer experiences, developing the future of work, and encouraging a data-driven culture are all common digital transformation themes. Leaders should define new KPIs and OKRs that help people understand the objectives and recognize how their work contributes to the organization’s transformation goals.

But there are common pitfalls, such as selecting the wrong KPIs, monitoring too many metrics, or not addressing poor data quality. “Having bad data, or an inability to realize the value and take action from data, is a surefire way for a digital transformation project to go south quickly, says Dwaine Plauche, senior manager of product marketing at AspenTech. “Without useful, contextual data that can be scaled and used throughout the organization, digital transformation efforts may simply become one-off  projects that get stalled at the pilot phase, leading C-suite leaders to believe the technology was a failure or the investment was a waste.”

This derailment stems from having no defined data strategy or having one not aligned with digital transformation objectives.

Consider how it looks to nontechnical executives when every digital transformation initiative has customized dashboards, different KPIs, and metrics with underlying data quality issues. Instead of initiatives telling a cohesive story, it leaves results open to interpretation and challenges. The data strategy should include guidelines on the types of KPIs, standards for dashboarding metrics, and responsibilities for improving data quality.

The five derailments I focus on here fall within the CIO’s responsibilities to address. They are important for CIOs leading multiple transformation initiatives to deliver against several business strategies. The practices that worked when digital transformations started small with one initiative must evolve into a digital culture and a transformation operating model. It’s in this transition where increasing derailments can lead to digital transformation failures.

Digital Transformation

Recently, we visited with several dozen CIOs and IT leaders across all industries to learn more about the challenges they are experiencing in their current transformation initiatives. The focus of our discussions was on promoting and enabling digitally driven outcomes and quicker business decisions. The conversations reminded everyone that there isn’t a one-size-fits-all approach to the journey and that each organization should focus on its operating model, the architecture of the organization, and the availability, accessibility, and necessity for data to help inform the decision-making processes.

A few key themes emerged:

Legacy technology continues to hinder the ability to operate at the pace business needs. The complexity of an organization’s application landscape, along with the lack of perceived value in modernizing core applications to introduce new capabilities and enhance existing capabilities, introduces risk to both internal colleagues and external customers. Organizations struggle with trade-off decisions on the ROI to move to the cloud while upskilling their IT organizations to support the new capabilities.

The voice of the customer needs to be core to the ability to align business and technology in delivery. Without attributing IT investment and IT development to the value it drives for the business, organizations struggle with delivering meaningful capabilities to the internal organization and their external customers. The risk of shadow IT and the loss of faith in IT’s ability to deliver to the enterprise creates redundancy in the environment, rogue decision-making in application investment, and overburdened cost and complexity in running the organization.

While the organization wants access to more data, more frequently, there are challenges with exposing all data without the proper business cases. While data is one of the strongest assets of an organization, exposing that data for meaningful decision-making comes with challenges. How much data does technology expose to the business? What is their confidence in the quality of the data? How do companies ensure the data used by the business has the right governance around it to have a common meaning across departments? Does all data need to be tied to a business case? Our discussions highlighted a variety of challenges – including the concern that the business truly does not have the right business cases in mind to give technology direction in what type of data would fulfill the needs.

Forward-looking organizations are leveraging the promise of productizing their data and investing in data governance as a key to that productization, whether for internal use or for opportunities to monetize/commercialize data products. Organizations with strong data governance practices are better equipped to empower citizen data scientists/analysts and enhance the speed and effectiveness of decision-making.

There isn’t a simple solution to these themes. Having the right technology operating model for the organization, coupled with the right governance processes and equitable representation in strategic decision-making, is a foundational step toward enabling technology to be a partner to the business. Leveraging that operating model to align strategic objectives to business requirements and technology capabilities will allow organizations to deliver using existing technologies while also building a roadmap of technology investment that is transparent and drives trust and an improved partnership.

Additionally, organizations should seek out the voice of the customer by understanding how the delivery of products and services aligns with the desires of an ever-fragmented customer journey. Defining customer journeys for both internal customers of technology and external customers of products can help identify moments in that journey where technology or process can have a significant impact. Business architects in the technology organization can bridge the gap between business domain leaders and technology experts and speak a core language that’s common between the domains.

From a data perspective, not every data request needs to be tied to a business case, but providing the guardrails around how data is used for exploratory purposes vs exposing data to make decisions that can alter the business of the organization is important. Developing data architectures that align to the organization’s broader enterprise architecture standards and collaborating with the enterprise to educate them on the sources of data, the quality of the data, and the governance around the data can improve the business domain’s confidence in the decisions or analysis done with the data.

Read the results of Protiviti’s Global Technology Executive Survey: Innovation vs. Technical Debt Tug of War  

Connect with the Authors

Sharon Stufflebeme Managing Director, Technology Consulting

Sandip Shah Managing Director, Technology Consulting

Digital Transformation

When Brad Clay became chief digital officer of GlobalFoundries in early 2021, he knew his role would be less about technology implementation and more about process change.

In 2018, the $8 billion global semiconductor manufacturer announced a pivot in its business strategy: The company would no longer develop and produce 7-nanometer and smaller chip technologies; instead GlobalFoundries would focus on producing specialized chips for high-growth markets such as automotive, 5G, and the internet of things.

“When we shifted from commodity contract wafer manufacturing to delivering more value to the device manufacturers, we faced a different set of business problems,” says Clay. “We had to align our business processes with the new strategy.”

Wholesale shift in process management

GlobalFoundries grew up from a collection of companies, each doing things differently, so processes had become siloed and fragmented, with no single person or organization accountable for an entire process. This, along with the change in business strategy, required a wholesale shift to global process management.

Clay, who is also CIO, worked with the IT team to spearhead development of a global business process owner model. “We wanted to understand and define how our processes could be interconnected and work end to end,” he says. “We had to break down the silos that naturally occur between finance, planning, and supply chain, for example. We did not start with an organizational construct; we started with a process construct.”

Once the global process model was defined, the technology team would create two common platforms, one for global processes and the other for data, but they could not put the cart before the horse.

“When you start a transformation, everyone wants a quick win,” says Clay. “We resisted that approach. We spent a year developing, defining, and visioning our new process model before we bought any software. That approach has paid huge dividends.”

Introducing a new role: Global process business owner

Clay and his senior executive peers identified eight global processes: idea to product, hire to retire, order to cash, demand to deliver, source to pay, market to contract, make to order, and record to report. They then identified people for a new role, global process business owner (GPO), which would be the linchpin to the new model.

In companies that have a relatively clear understanding of their global processes, that GPO might be a Six Sigma Black Belt with a continuous improvement lens, but this was not the case with GlobalFoundries. “Because the concept of global business processes was new to us, we needed VP-level leaders to step into the new role. We had to drive the transformation from the top down.”

Taking on a GPO role is not for the faint of heart. Clay needed the newly appointed leaders to understand the magnitude of the change they would drive. “We communicated that this was not a continuous improvement effort where the owner would make the process 5% better,” he says. “Our message was that transformation starts at 50%, and that our leaders had to have the vision and courage to sign up for that level of improvement. Anyone will sign up for 5%; it’s in the margins. But 50% is where people get nervous. That’s a very visible level of accountability.”

Once process owners were identified, they went through training so they could have a common understanding of processes, lexicon, and ways of interacting. “We even did 360-degree assessments on the leaders, because we needed the process owners to be a tight-knit group,” says Clay. “They would be accountable for driving common process through the company in a way that had never been done before.”

Under each GPO are process advisory groups that span the various departments involved in a single global process and have a stake in its improvement. Because a GPO cannot have detailed knowledge about every single piece of a process, these advisory groups are critical to making the global process owner model work.

“The advisory groups ensure that the GPO understands the user stories, and they make sure that everyone knows what is going on with the processes,” says Clay, who also reorganized IT so each GPO has a dedicated technology owner.

With the GPO model in place, Clay and his IT team could now address the challenge of implementing new software to automate the global processes. “We had primarily been using point solutions for specific requests held together by manual effort,” he says. “We had to cross ‘the gap of stranded investment’ and focus on platforms. We replaced pretty much everything — ERP, CRM, PLM, quality management — new software soup to nuts.”

GPO lessons learned

Now that Clay can see the faster decision-making and increased productivity that has resulted from the GPO model and platform architecture, he has some lessons to share.

The first: Transformation is more than software implementation. GlobalFoundries’ GPOs are aware that transformation has two elements: digital enablement and business change, which ensure that your operating model is aligned with the business strategy.

“That is why the GPO has to be a senior person,” Clay says. “The GPO aligns the processes to the corporate strategy and then makes sure that what IT is building into the platform aligns. I believe that digital transformations fail because its leaders miss that duality.”

The second lesson is that when you implement the software, minimizing customizations helps you avoid “fighting gravity.” Clay sometimes gets up in front of his colleagues and drops a rubber ball to make the point that when you choose to veer from a vanilla ERP, for example, you are trying to keep the ball in the air.

“Commercial software was built by people with expertise in business processes,” he says. “When you decide to customize the software, you are deciding about whether you are removing friction or fighting gravity. Our goal is to fight gravity only where we absolutely have to.”

Finally, Clay points to the importance of senior-level support and business engagement.  Early on in the transformation, hundreds of people across the entire global company came together to walk through each process, with each GPO standing up to address plans for their own area. “It was the global process owner explaining how processes are going to change,” he says. “It wasn’t an IT person explaining how SAP works.” That, and the fact that CEO Dr. Thomas Caulfield described the program as “business transformation enabled by IT,” were critical to the program’s success.  

“At GlobalFoundries, we manufacture semiconductor chips in four different facilities across three continents,” says Clay. “But the GPO model was a true transformation, which we had never done. And that’s the challenge of transformation. It’s always unique.”

Business Process Management, Digital Transformation

Thanks to cloud, Internet of Things (IoT), and 5G technologies, every link in the retail supply chain is becoming more tightly integrated. These technologies are also allowing retailers to capture and gather insights from more and more data – with a big assist from artificial intelligence (AI) and machine learning (ML) technologies – to become more efficient and achieve evolving sustainability goals.   

From maintaining produce at the proper temperature to optimizing a distributor’s delivery routes, retail organizations are transforming their businesses to streamline product storage and delivery and take customer experiences to a new level of convenience—saving time and resources and reinforcing new mandates for sustainability along the entire value chain.

“Transformation using these technologies is not just about finding ways to reduce energy consumption now,” says Binu Jacob, Head of IoT, Microsoft Business Unit, Tata Consultancy Services (TCS). “It’s also about being able to capture the insights needed to better forecast energy consumption in the future.”

Reducing energy consumption across the value chain

For example, AI/ML technologies can detect the outside temperature and regulate warehouse refrigeration equipment to keep foods appropriately chilled, preventing spoilage and saving energy.

“The more information we can collect about energy consumption of in-store food coolers, and then combine that with other data such as how many people are in the store or what the temperature is outside, the more efficiently these systems can regulate temperature for the coolers to optimize energy consumption,” says K.N. Shanthakumar, Solution Architect – IoT, Retail Business Unit, TCS.

Landmark Group, one of the largest retail and hospitality organizations in the Middle East, wanted to reduce energy consumption and carbon footprint, improve operational excellence, and make progress toward its sustainability goals. Working with TCS, Landmark Group deployed TCS Clever Energy at more than 500 sites, including stores, offices, warehouses, and malls, resulting in significant improvements in energy efficiency and carbon emissions at these sites.

“Retail customers are looking to achieve net zero goals by creating sustainable value chains and reducing the environmental impact of their operations,” says Marianne Röling, Vice President Global System Integrators, Microsoft. “TCS’ extensive portfolio of sustainability solutions, built on Microsoft Cloud, provides a comprehensive approach for businesses to embrace sustainability and empower retail customers to reduce their energy consumption, decarbonize their supply chains, meet their net zero goals, and deliver on their commitments.”

Optimizing delivery workflows

For delivery to retail outlets, logistics programs—TCS DigiFleet is one example—increasingly rely on AI/ML to help distributors plan optimized routes for drivers, reducing fuel consumption and associated costs. Video and visual analytics ensure that trucks are filled before they leave the warehouse or distribution center, consolidating deliveries into fewer trips. Sensors and other IoT devices track inventory and ensure that products are safe and secure. Postnord implemented this solution to increase fill rate, thereby improving operations and cost savings. 

“Instead of dispatching multiple trucks with partially filled containers, you can send fewer trucks with fully loaded containers on a route that has been optimized for the most efficient delivery,” says Shanthakumar. “5G helps with the monitoring of contents of the containers and truck routes in real time while dynamically making adjustments as needed and communicating with the driver for effective usage.”

More data, better insights

With cloud-driven modernization, intelligence derived from in-store systems and sensors can automatically feed into the supply chain to address consumer expectations on a real-time basis. In keeping with the farm-to-fork movement, for example, consumers can scan a barcode to find out where a product originated and what cycles it went through before landing on the grocery store shelf.

With 5G-enabled smart mirrors, a person can virtually try on apparel. By means of a touchpad or kiosk, the mirror technology can superimpose a garment on a picture to show the shopper how it will look, changing colors and other variables with ease.

Retail transformation enabled by AI/ML, IoT and 5G technologies is still evolving, but we’re already seeing plenty of real-world examples of what the future holds, including autonomous stores and drone deliveries. The key for retail organizations is building a cloud-based infrastructure that not only accelerates this type of innovation, but also helps them become more resilient, adaptable, and sustainable while staying compliant, maintaining security, and preventing fraud.

Learn more about how TCS’ Sustainability and Smart Store solution empowers retailers to reimagine store operations, optimize operational costs, improve security, increase productivity, and enhance customer experience.

Cloud Computing, Digital Transformation, Retail Industry

Digital transformation has always been a continuous journey, one that should become an organizational core competency, with the introduction of digital services an ongoing imperative to evolve the business and stave off disruption.

While this may remain the case, subtleties are emerging about how digital transformation should be thought of, impacting how it should be undertaken. Within these schools of thought, what was once called digital transformation should now be viewed as business transformation because such initiatives encompass so much of the way organizations operate, and because technology alone does not a transformation make.

It’s that latter point that may be the biggest change in our perception of digital transformations. A framework for thinking about digital initiatives today is part digital strategy (new capabilities, new markets, and new products), part technology aligned with the strategy, and an ability to adapt to and adopt new processes, resources, and ways of working, according to Deloitte.   

“If you can only do one thing, focus your efforts on technologies aligned to strategy because it drives superior market value,’’ the firm says. 

With that in mind, here are five strategies, approaches, and technologies around digital transformation that are hot and two that have gone cold.

Hot: Debate about the term ‘digital transformation’

Depending on whom you ask, the very concept of digital transformation is either still the raison d’être of IT today — or it’s becoming a thing of the past. And while the discussion around this can seem semantic or even pedantic, there are meaningful impacts arising from the debate.

At Schneider Electric, “we don’t even use the term ‘digital transformation,’” but rather, ‘business transformation,’ says senior vice president and CIO Bobby Cain, who came from the business side of the company. “In order to transform how you work, the business has to lead the transformation.”  

Bobby Cain, SVP and CIO, Schneider Electric

Schneider Electric

Melanie Kalmar, corporate vice president, CIO, and chief digital officer of Dow, agrees. Speaking in a recent Gartner webcast, Kalmar said that digital transformation goes beyond technology. Further, IT is not going to drive digital transformation on its own, she said.

“The previous perception of being digitally driven was that IT would lead all of the change and that technology would be the driver,’’ Kalmar said. “Digital transformation is really about how people do their work differently and understanding IT wasn’t going to drive this on our own.”

She referred to digital transformation as “a team sport.” At Dow, each business now owns its digital strategy, and digital leaders have been placed in the business units to ensure data quality.

But Isaac Sacolick, founder of digital consultancy StarCIO, believes business transformations are more about mergers and acquisitions and outsourcing, and that digital, AI, and analytics fall under the purview of IT, so CIOs are expected to continue leading digital transformations. Results from the State of the CIO survey concur, as 84% of IT leaders say CIOs are more involved in leading digital transformation initiatives compared to their business counterparts. Moreover, 72% of line of business leaders agree.

Jim Ruga, CIO of Fictiv, a quote-to-order manufacturing provider for mechanical parts, says a lot of businesses in the manufacturing industry struggle with digital transformation because business leaders view it in the context of buying a big ERP system and expecting it to solve a problem.

Melanie Kalmar, CVP, CIO, and chief digital officer, Dow


“It’s the threading together of these systems [and] processes where decisions are made by humans, and you have to introduce machine learning and AI and glue them together to make these things effective,’’ he says. “It’s no longer just buying the software and ‘Wow, we’re digital.’”

Instead, IT needs to take these large systems and make them smart to realize the gains and benefits of labor or cost reduction, Ruga says. “You don’t get that by implementing systems off the shelf.”

Cold: The how of hybrid work

The concept of hybrid work, new for the majority of organizations when the effects of the pandemic reached a point where people started returning to the office on a part-time basis, is far less novel of late, and as such initiatives aimed at making it work have cooled since their apex just a year or so ago.

“People have figured it out based on the resources they have and the tools they have to support it,’’ Cain says. “Honestly, it’s becoming a tiresome conversation. I think it’s losing its relevancy.”

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. 

Dean Kontul, EVP and CIO, KeyBank


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.

Berke Menekli, SVP of digital platform services, 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.”

More on digital transformation:

What is digital transformation? A necessary disruption10 ways to accelerate digital transformation7 secrets of successful digital transformations8 reasons why digital transformations fail7 digital transformation mythsDigital KPIs: Your keys to measuring digital transformation success

Digital Transformation, IT Leadership, IT Strategy

Chris Richner signed on as CIO of Norco Industries with a clear mission: To guide the US-based manufacturer through wholesale digital transformation.

“I was brought on board to be a change agent,” says Richner, who is now 18 months into the job. “The first order of business was to get my infrastructure shored up, because the end goal in my five-year plan is to bring digitalization to the shop floor.”

Norco manufactures a range of recreation vehicle (RV), industrial, and automotive products under seven brands, including Adnik (seating systems), Bal RV (RV components), Norco Professional Lifting Equipment (floor jacks, clutch jacks, transmission jacks), Flo-Dynamics (fluid maintenance equipment), Nortool (machining and tooling equipment), Norcoat (e-coat and powder coat finishing), and Freedom Industrial Hydraulics (industrial lifting equipment).

The manufacturing industry is undergoing seismic change due to increased digitization and other IT advancements, and CIOs are at the center of this, with 86% of manufacturing IT leaders saying their role is becoming more digital and innovation focused, and 84% agreeing that the CIO is becoming a changemaker, according to the 2023 State of the CIO survey.

At Norco, Richner is stepping up with an aggressive plan to transform the company’s technology infrastructure within his first five years. But embracing new technology wholesale is a tall order. So Richner hit the ground running with a plan to use robotic process automation (RPA) to free the company’s staff from time-consuming, repetitive tasks, giving them the bandwidth to embrace broader change.

RPA uses technology, business logic, and structured inputs to automate business processes. Richner sat down with Norco Industries CEO Michael Tallman to discuss how the company could leverage RPA and to determine possible use cases to prove its utility. Together they decided the finance department was the perfect choice.

Proving the pilot

Richner’s team worked with finance to identify workflows that could most benefit from the technology, and then took those workflows to RPA vendor Kognitos to help create automation plans. They decided to use RPA to power the entire accounts receivable and accounts payable (AR/AP) process, including billing and invoicing.

“We have a lot of repetitive tasks, things that are error prone,” Richner says. “No one wants to do those tasks. They don’t want to scan documents all day.”

The resulting automation enabled Norco to save 10-15 hours of employee time per week, eliminate 15-20 hours of billing tasks per week, and remove 30 hours of invoicing tasks per week, while reducing human error and hiring needs. Even nontechnical employees were able to use the Kognitos platform to check processes and verify the automations were working correctly, Richner says.

Here, the platform’s ability to use natural language has been beneficial, Richner notes.

“The philosophy in RPA has been we need to teach humans how to talk to machines,” says Binny Gill, founder and CEO of Kognitos. “That is not scaling well because it’s a hard thing for most of us to think like a machine. It’s alien.”

Human brains, Gill notes, are expert at handling ambiguity, whereas machines struggle with it. Like ChatGPT and other generative AI, Kognitos relies on conversational exception handling, reaching out to human users and asking for clarification and additional information where necessary.

Envisioning RPA possibilities

With the experience of building the finance automation under their belts, Richner and Tallman decided to expand the effort, bringing in Norco’s two division presidents and the director of human resources for an envisioning workshop on RPA.

“We came up with a total of 16 different workflows that we could leverage and some of them are fairly significant — major impact,” Richner says. “Generating a bill of materials is a big one, because there’s a lot involved in how we generate them off design specs.”

One of the things that sets Norco apart from many of its competitors is that it engineers on request. A customer might want to change the design of the RV that sits on top of a Norco frame, making it wider, for example. That customer would submit those changes to Norco, who would then engineer to the new specs and come back to the customer with a design and price quote.

Today, Richner explains, that’s a highly manual process involving somewhere between 12 to 15 steps, three or four employees, and lots of back and forth. RPA could allow Norco to automate the entire process. Customers could make changes to their designs in real-time in a customer portal. RPA could then generate the bill of materials from those design specs, generate a master table from the bill of materials, feed that master table into solid modeling CAD engineering application SolidWorks, and render the design in real-time. The system could then present the new design back to the customer in the portal with a price quote.

“That’s a game-changer right there,” Richner says.

There are other plans too. For instance, Norco’s human resources department is active in monitoring social media.

“What if I had an AI engine that could go do that for me? We don’t want it to do an automated response because we want the response to come from us, but at least it’s finding it for us,” Richner says.

Onboarding and offboarding employees, processing checks, and handling chargebacks from freight are all additional opportunities.

“We’re at the very beginning and have a long way to go,” Richner says. “The next step is getting APIs and AI wrapped together and doing some off the charts stuff.”

To his peers getting started with RPA, Richner says, “Don’t be scared. Spend the time to understand it.” You don’t have to be an expert, he says, but learn the basic concepts, find a good partner, and go through an envisioning process with your stakeholders.

“They’ve got to buy into it as well,” he says. “If you start there, it’ll happen. And once it starts to happen, it just snowballs and gets bigger and bigger.”

Digital Transformation, Manufacturing Industry, Robotic Process Automation

Digital transformation has embedded IT at the center of business strategy, making all organizations technology enterprises today, irrespective of their industry. Business processes, culture, workflow, and systems are all necessarily impacted by digital transformation efforts, which by definition overhaul how business gets done, expediting efficiencies, modernizing the enterprise, and — when executed well — enhancing profitability.

It’s little wonder then that CEOs across the world are attaching high importance to digital transformation as a means for achieving their future goals. According to KPMG’s latest 2022 CEO Outlook survey released in January 2023, 72% of the 1,325 CEOs across 11 markets have an “aggressive digital investment strategy, intended to secure first-mover or fast-follower status.”

But driving radical change in any enterprise without a well thought out strategy is a recipe for disaster. Before embarking on digital journeys, IT leaders must address several key areas that could otherwise stymie the entire process.

Unfortunately, the following planning, or ‘phase 0,’ mistakes are too often made by IT leaders looking to move forward with digital implementations before they are truly ready to make good on investments.  

Failing to secure LOB bandwidth

IT leaders must first gauge the readiness of their organizational engine to drive digital transformation. Without adequate resources, intentional change can quickly become chaotic. Resource assessment is a vital phase 0 or even phase -1 process of any digital initiative.

Most digital transformation initiatives fail because of lack of resources. While IT leaders often focus on planning, evaluation, partnerships, and platforms, they often forget to assess the human resource bandwidth required to implement, execute, and make good on the completed program — in particular within the lines of business (LOBs) impacted by by digital transformation.

No digital initiative today can succeed without LOB sponsorship and involvement. For instance, if a company intends to overhaul its recruitment strategy with a new digital solution, there must be complete involvement of the human resource department. However, in most cases, the HR team already has its hands full with its day-to-day workload and is unable to take out time to work alongside IT on the project.

With low HR involvement in meetings and feedback phases related to the project, IT will struggle to hit goals and timelines, jeopardizing the initiative’s outcome.

While it is relatively easy for an IT leader to put his or her team in place before embarking on a digital transformation journey, it may not be as easy for LOB leaders to identify the right team members to be involved. Therefore, it is on CIOs to ensure that their LOB counterparts set aside the right talent from their departments to be involved in the process and prioritize their participation alongside their daily work. This must be done right at the start, not after the project has launched, else the CIO will have to continue to re-baseline the timing and requirements of the initiative. Cross-functional teams are vital to digital success, and CIOs should insist on them.

Misunderstanding the organization’s digital maturity

Another major reason digital transformations stumble is the lack of visibility business and technology leaders often have into their organization’s digital maturity before they begin. To become digitally mature, an enterprise must know its capabilities. This is an imperative precursor before deciding to go digital.

Each company has a different level of digital maturity at the enterprise, technology, and functional levels, and how it complements business. If business and technology leaders understand where they stand on this digital maturity curve, it gets easier to know where they intend to go and how long will it take to reach that destination.

The onus lies on the CIO to apprise top management on the status of the company’s digital maturity, so they know where they stand. For instance, if a company is in growth mode, it may need to align resources, scale up its technology platforms, and hire more employees. By getting to know the digital maturity in each of these functions, technology investments can be prioritized and aligned in relevant areas accordingly. In the absence of this, companies can make investments in wrong areas without realizing larger value.

Some questions CIOs can ask as part of the digital maturity discovery process could be: Does the company have a clear strategic vision, objectives, and direction? How does the company rank (laggard, mediocre, or leader) against its competition? How consistent is the organization’s digital experience across various channels?

To get more visibility into digital maturity, CIOs would be wise to create digital maturity indexes and link them to various facets of the business.

Launching without a clear mission

Any digital journey kicks off with a problem that is worth solving. It would, therefore, help if there is a single, clear statement that throws light on the problem at hand, those experiencing it, and the reasons to solve it. IT leaders may come up with lengthy project briefs and comprehensive RFPs but without a clear, precise problem statement they are all no good.

A well-honed problem statement provides clarity for all involved. Deep into the complexity of a transformation, team members can return to this document for guidance, using it to help address drift or any additional issues or questions that may arise along the way to ensure they stay on course and on mission. A clear problem statement can also be helpful if a technology leader has taken up three or four projects simultaneously, as it can help with prioritization issues and any overlapping complexities that might arise to help ensure each project is successful.

A simple exercise such as a drawing board session can go a long way in understanding the pain points of the relevant stakeholders and coming up with a refined problem statement. A couple of weeks of such a collaborative process, prior to getting into a long-drawn digital initiative, can help business and IT to get on the same page and ensure they stay focused on delivering the optimal outcome regardless of what they encounter along the way.

Digital Transformation

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The emphasis Huawei has placed on a wave of investment in optical fixed line networks is bearing fruit. At MWC 2023, the company unveiled a range of F5G
(Fifth generation fixed network) solutions for vertical industries. For Gu Yunbo, who manages the part of Huawei that sells optical network products to enterprises, this is the start of something big: a new wave of “green technology and digital transformation”.

Since 2020, Huawei has been working with industry parties on nurturing emerging standards for all-optical F5G. The reason for this investment in F5G includes spiraling traffic volumes on existing fixed line networks, caused by the roll-out of 5G and continuing digital transformation efforts.

Huawei describes F5G as “future-oriented strategic infrastructure”. Gu foresees widely available “ultra-high bandwidth, with optical networks directly connected to desktops, Wi-Fi access points and [IoT] machines”. For end users, he describes the result as having “almost zero latency and zero jitter.”

According to the management consultancy EY, global expenditure on F5G is growing at a rapid pace (18% CAGR). By 2025, EY expects the market to be worth over €400bn annually.

Much of the demand for fiber networks comes from consumer-facing industries (including cloud-based gaming, AR/VR, UHD video, smart transportation and smart home applications).

But Gu also sees F5G opening up new possibilities for employee productivity and digital transformation.

Gu says: “Huawei has released five solutions for digital transformation scenarios in various industries. These include campus networks, WAN production networks, industrial IoT, data center interconnects, and all-optical sensing solutions.”

At MWC, Huawei unveiled a 50G POL prototype designed to upgrade campus networks. Initially, the aim is to support the roll-out of ultra-fast “Wi-Fi 7-oriented” green campus networks, particularly in educational and healthcare scenarios.

“In practice,” says Gu, “we find that although 10G PON can meet campus requirements in most cases, the rising use of AR/VR teaching, 3D medical imaging, and remote interactive office poses new requirements and challenges on network bandwidth and latency.”

Huawei has also been working on digital transformation projects that directly rely upon optical networking scenarios. In electrical power generation, for example, optical F5G networks, alongside video and sensors, will play a key role in enabling remote inspection of power lines.

To underpin solutions like this, Huawei unveiled the industry’s first end-to-end OSU product portfolio at MWC. Gu describes the portfolio as “building a reliable optical communication base” for energy, transportation and other industries.

In the interview, Gu also described three additional optical-related launches at MWC. These included a lossless industrial optical network solution to improve working conditions and efficiency in large-scale industrial scenarios and a high-precision optical-visual solution for perimeter inspection at large facilities such as railways and airports.

In a sign of things to come, Huawei has also been building F5G solutions for the data center, including storage-optical interconnects (SOCCs) for financial transactions where speed and reliability are at a premium.

“We are continually working with industries to promote wide application of F5G in various industries,” said Gu. “We believe that F5G, as it evolves, is going to strengthen the level of innovation and reshape productivity.”

Find out more about Huawei’s optical solutions here.

Digital Transformation