- Change
- Change, Change Management, IT
- 5 min reading time
Gabriel Grieder
On average, companies realize less than one-third of the expected benefits from digital transformations (McKinsey, 2023). New tools, systems, and platforms are introduced, but after only a short time, no one is using them anymore. The obvious answer would be: The technology wasn’t good enough. That’s wrong. Systems often work well—but they aren’t used, aren’t accepted, and aren’t integrated into decision-making. In this wiki, our authors* demonstrate that tools no one uses end up costing more than their initial purchase price. They represent a missed opportunity.
Table of contents
1. IT Change Management: The Real Problem
Over the past ten years, I have had the opportunity to support numerous analytics, reporting, planning, and transformation projects, both as an external consultant and in various line management roles. Time and again, the same pattern emerged: tool implementations are often set up properly, meticulously planned, and executed. However, change management is where things fall short. Change management is often mistakenly viewed merely as a communication measure, rather than as a key prerequisite for the success of an implementation project. Success, however, does not come from implementation alone, but rather when the new systems are actually put to use.
2. The Most Common Mistakes Made During Tool Implementations
Practical experience and research consistently show the same pattern: tool implementations rarely fail because of the technology itself, but rather because of the same five mistakes that Kotter (1996) had already identified.
- Change starts too late. The implementation is planned, built, and tested, and users aren't involved until shortly before go-live. The result: a disconnect from the solution and a lack of ownership.
- Communication is sporadic. Kick-off, presentation, training. Then things go quiet. What’s missing is ongoing communication that explains: What, specifically, will change for me in my day-to-day life?
- Focus on training rather than application. Users learn about functions, menus, and reports, but not when to use them, why they are relevant, or what value they add. This is knowledge without application (Kotter, 1996, p. 14).
- Lack of clear accountability. Change is viewed as a project, not as an ongoing responsibility. If it is unclear who is responsible for ensuring adoption, it simply does not happen.
- Success remains invisible. Adoption isn't measured, and usage isn't managed. Without KPIs, there is a lack of transparency, control, and momentum.
3. What Really Works: 3 Levers for the Sustainable Adoption of IT Change Management
The key difference between this and successful change management lies primarily in the way change is initiated and supported.
Lever 1: Involve people early on.
The first—and probably most important—point is urgency. This involves actively ensuring that changes are tackled seriously. People tend to systematically overestimate their own competence. In academia, this is known as the Dunning-Kruger effect. The better you assess your own position within the company, the less need for action you see. This has nothing to do with malice, laziness, or poor leadership; it is simply a lack of ability to recognize one’s own shortcomings (Kruger & Dunning, 1999). Those who are involved early on develop a sense of ownership. Those who are only informed at the end develop resistance.
Lever 2: View communication as an ongoing process.
Equally crucial is how clearly a vision is communicated, because only what is understood can be implemented. What matters is not just what is communicated, but how. Pressure and external rewards undermine intrinsic motivation. As soon as the pressure disappears, the behavior disappears (Deci, 1971). People must want change, not be forced into it. Actions speak louder than words; this applies just as much in life as it does in IT change management. Visions must be backed up by concrete actions; only then can genuine motivation develop within the team.
Lever 3: Make Success Visible.
Behavioral change takes time. In IT change management, this means that employees must first become familiar with new systems and processes before they can actively apply them in their day-to-day work. It can take months or even years for a change to become firmly established. Pressure to implement changes often results in new software or processes being used out of obligation rather than conviction. Only when employees experience concrete improvements—such as more efficient workflows, fewer errors, or better collaboration—over an extended period of time will the new behavior be adopted permanently. That is why successes should be regularly highlighted and communicated. Obstacles should not be viewed as threats. On the contrary, they provide valuable insights for further improving training, processes, or systems.
4. Classification Using the ADKAR Model
Successful transformations can be managed using the five dimensions of the ADKAR model (Hiatt, 2006).
- Awareness: Employees need to understand why the change is necessary. In analytics transformations, this means that the added value of new analytics tools must be presented in concrete and tangible terms, not abstractly.
- Desire: The willingness to participate is a personal decision. It does not arise from pressure, but from trust. Trust develops when employees realize that decisions will be made based on the new analytics solution rather than on gut instinct. Managers who admit that they themselves do not yet fully understand a new tool build more trust than those who feign unfounded confidence to the outside world (Nienaber, Hofeditz & Romeike, 2015).
- Knowledge: Through clear change management communication, employees know how they should adapt. However, simply knowing how to use a tool is not enough. What matters most is that they know which analytics data matters and when, and what decision-making process underlies it. This is different from mere proficiency with analytics tools. Kotter’s 8-step model provides the framework here: develop a vision, communicate it, and remove obstacles (Kotter, 1996).
- Ability: Knowledge is put into action. A team that understands the logic behind a new analytics tool but never uses it in a real decision-making situation hasn’t brought about any change yet. Change takes time, practice, and patience—and the realization that a one-time training session isn’t enough.
- Reinforcement: The change is being embedded. If a decision is demonstrably made based on the new analytics data, this should be highlighted and celebrated. If you stop reinforcing it, you risk employees falling back into old structures and behaviors.
5. Practical Relevance: Lessons Learned from Analytics Transformations
The difference between successful and unsuccessful analytics implementations always comes down to the same questions: Is the solution being actively used? Does it change decision-making processes? Is it perceived as adding value? In practice, the key to success almost never lies in the tool itself, but rather in the interplay of communication, behavior, and management.
Change management runs like a common thread through all phases of the implementation process—from functional design to embedding the process after go-live. If you don’t start this process until go-live, you’re starting too late.
6. Conclusion & CTA
Change management is not an add-on. It is the key success factor in any transformation. Value is not created during implementation, but through consistent use. Consequently, technology is rarely the problem. Change management in IT is not a technology project; it is a people project. Overconfidence, a lack of trust, pressure instead of persuasion, and obstacles that are not understood—these are the real stumbling blocks. Successful IT change management starts with people, not with the system.
Do you want to ensure that new analytics systems not only go live but are also actually used?
Then talk to us here about IT change management: from stakeholder alignment and communication to adoption KPIs and sustainable integration into everyday work.
Sources
Kotter, J. P. (1996). Leading Change. Harvard Business Review Press.
Kruger, J., & Dunning, D. (1999). Unskilled and Unaware of It. Journal of Personality and Social Psychology, 77(6), 1121–1134.
Nienaber, A. M., Hofeditz, M., & Romeike, P. D. (2015). Vulnerability and Trust in Leader-Follower Relationships. Personnel Review, 44(4).
Deci, E. L. (1971). Effects of externally mediated rewards on intrinsic motivation. Journal of Personality and Social Psychology, 18(1), 105–115.
Troy, A. S., Shallcross, A. J., Brunner, A., Friedman, R., & Jones, M. C. (2017). Cognitive reappraisal and acceptance. *Emotion*, 18(1), 58–74.
Hiatt, J. M. (2006). ADKAR: A Model for Change in Business, Government, and Our Community. Prosci Learning Center.
McKinsey & Company (2023). Three New Mandates for Capturing the Full Value of Digital Transformation.
*Authors: Gabriel Grieder and Adrian Stenger (both of s-peers AG)
