Digital transformation: how to get the organization on board

Three-quarters of digital transformation initiatives are stuck in “pilot purgatory.” Why are so many projects unable to scale their digital systems to the enterprise level?

While technical boxes may be ticked, organizational adoption – whether and how employees welcome change – is often overlooked. Getting real buy-in from people is a much more complex challenge than installing hardware or software. Go figure.

[ Also read Digital transformation: 5 reality checks before you take the plunge. ]

In our experience, there are four common barriers to organizational adoption. As an IT manager, ask yourself these questions:

  • How do you help your employees visualize a new “everyday” and make them comfortable with these changes without fear of job insecurity?
  • How are you strengthening and reskilling your existing talent so that data skills are pervasive in your organization?
  • Where can you revise your organizational structure to encourage collaboration rather than competing priorities that slow the project down?
  • What processes can you institute (or improve) that will enable a faster rate of change so that your business can learn continuously and organically?

Role change and job security

Most people don’t readily accept change, especially when it comes to a work disruption. Recent research on trends in job security and automation shows that around a quarter of people are worried about “AI taking their job”.

Leverage those who will be most impacted to shape the future of the organization, creating champions and advocates for change along the way.

This percentage is lower than it was a few years ago, thanks to a better understanding of the human role in the workplace of the future, but it still calls on CIOs and IT managers to think carefully about how they communicate changes to valued employees.

Consider the employee who typically spends many hours a week collecting data and creating reports. Their natural responses to a new digital tool will almost certainly be fear of reduced job security if their concerns are not addressed directly. For these employees to embrace modern technology, there must be an incentive.

For starters, as systems are connected and processes are digitized, many information-based tasks that were once done manually, such as data collection and reporting, are becoming automated. This frees up their time to focus on more strategic, meaningful, and high-level tasks. It is not a question of replacement but of evolution. The employee’s role will shift from repetitive tasks to more analytical and problem-solving work.

[ Read also: Automation vs. IT jobs: 3 ways leaders can address layoff fears ]

Defining these new roles doesn’t have to be a strictly top-down decision. Implement a proactive change management strategy to engage all affected employees early in the process. Incorporate employee feedback into the organizational design solution and process, leveraging those who will be most impacted to shape the future of the organization, creating champions and advocates for change along the way.

Rethinking the approach to talent needs

Data analysis doesn’t always require data scientists. CIOs and IT managers often reach a turning point when they discover that most employees can be trained to become resident data analytics experts. When employees combine new knowledge of data analytics with their existing knowledge of processes or machines, they can quickly be at the forefront of a digital journey.

When employees combine new knowledge of data analytics with their existing knowledge of processes or machines, they can quickly be at the forefront of a digital journey.

That’s good news for most IT managers, simply because the demand for data science and cybersecurity skills has skyrocketed. Upgrading the skills of existing team members can be key to achieving sustainable adoption and continuous improvements of digital solutions. This includes long-term improvements in employee engagement and retention, increased cross-functional collaboration, and the adoption of modern technology trends.

In addition to their technical skills, employees must be skilled in diagnosing and solving problems using the data now available to them. Employees who may have been data collectors before can become problem solvers based on new data-driven insights. Make sure your employees are ready to learn and grow to take advantage of these opportunities.

Effective collaboration between IT and operations teams

When two forces within an organization don’t want to work together, it can create immense friction. In the case of digital transformation, IT and operational technology (OT) priorities are often competing and misaligned.

For example, in a manufacturing context, OT and operations teams focus on improving plant productivity (i.e. making more products at lower cost). On the other hand, IT typically focuses on maintaining enterprise platforms and mitigating cyber risks.

Competing priorities can also result from how projects are funded. OT teams are often focused on solving problems in one factory and sometimes even challenged to compete against other factories within the same supply chain network. IT teams may be more interested in a scalable solution that benefits all factories but may not be able to fully fund a project.

When these two priorities are exclusive, it limits collaboration and delays the digital transformation process. However, adoption depends on effective collaboration between IT and OT teams: OT teams bring manufacturing process expertise and knowledge of data origin. IT teams ensure that business platforms and the required network infrastructure are reliable, scalable and secure.

To align the goals of IT and OT teams, consider formalizing dedicated digital transformation initiative teams with leaders and subject matter experts from the IT and OT functions. These cross-functional teams, jointly funded by operations, engineering, and IT, can collectively define initiative goals, collaborate on implementation plans, and champion change across the organization. They should have a common group of executive stakeholders, read progress together, and be rewarded together.

Enable a faster pace for learning and experimentation

To stay competitive in today’s digital world, organizations need to keep abreast of digital initiatives. They need to quickly extract lessons and apply those learnings to implement new features. Creating a culture that fosters continuous growth and learning opportunities is not only essential to the successful adoption of digital tools, but also to the continuous improvement of digital technologies through experimentation.

Learn more about digital transformation

Key characteristics of “learning organizations,” a concept popularized by Peter Senge, include systematic problem solving, experimentation, and knowledge transfer. Systematic problem solving involves generating a hypothesis, testing that hypothesis, and using data rather than hypotheses as the basis for decision-making. A minimum viable product (MVP) approach can be used to quickly test a hypothesis and generate data to assess the effectiveness of the solution. Using a common enterprise platform can allow you to quickly scale an MVP across the enterprise.

Digital transformation requires a shift in mindset – on how we respond to employee concerns, their desire to learn and acquire new skills, their ability to make high-level decisions, and their desire to experiment and solve problems. But too often, organizations are trapped in a box. They overlook the critical link between having the right technology and achieving a step change in operational productivity. When IT leaders ask people-centric questions, they can understand why their digital transformation initiatives are stalled and make the necessary changes to move those efforts forward.

[ Discover how priorities are changing. Get the Harvard Business Review Analytic Services report: Maintaining momentum on digital transformation. ]

Aubrey L. Morgan