Technology programmes are usually approved because an organisation wants something else: greater productivity, better information, lower cost, faster decisions, stronger customer relationships or a capability it does not possess today. Yet organisations frequently manage the technology as though implementation itself were the destination. A system can be installed successfully while the organisation around it continues to operate much as it did before.
This is where technology change becomes an executive question rather than an IT question. The value of a new system depends on what happens to authority, incentives, processes, judgement and behaviour once the technology arrives. When these remain largely untouched, organisations can spend heavily on modern technology while preserving an old operating model.
Executive Summary
Technology rarely creates organisational transformation by itself. New systems alter information flows, responsibilities, decision rights and sometimes the value of accumulated expertise. If leaders treat these consequences as secondary to implementation, they may achieve technical deployment without changing business performance.
Bennet Lientz and Kathryn Rea recognised much of this problem in Breakthrough IT Change Management in 2004. More recent digital transformation research has reached similar conclusions using a different vocabulary. The enduring executive issue is therefore less about managing a particular generation of technology than understanding the organisation into which that technology is being introduced.
In This Article
- The Technology Problem Is Often an Organisational Problem
- What Has Changed Since 2004, and What Has Not
- Technology Changes Authority as Well as Process
- Resistance Can Be Irrational, Rational or Informative
- The Business Case Is Realised After Implementation
- Standardisation Is an Economic Choice, Not a Technical Virtue
- Not Every Technology Project Is a Transformation
- What Senior Leaders Should Consider
- Questions for the Boardroom
- The Organisation Is Part of the Technology
The Technology Problem Is Often an Organisational Problem
Most technology programmes start with a recognisable business problem. Customer information is fragmented, reporting is slow, employees duplicate work, an enterprise system has become difficult to maintain, or management cannot obtain a reliable view of operations. Artificial intelligence has added another category of opportunity: activities that previously required substantial professional effort can increasingly be assisted, accelerated or automated.
The appeal of a technological solution is understandable, as it makes the proposed change tangible. Executives can approve a platform, budget a migration, establish milestones and measure implementation. Organisational problems are less accommodating. Trust cannot be migrated according to a project plan. Authority does not become clear because a new dashboard has been launched. Departments do not suddenly share information simply because a common database exists.
This distinction becomes important when the visible technology problem is actually the expression of an older organisational condition. Fragmented customer information, for example, may result from incompatible systems. It may also result from incentives that encourage commercial teams to protect accounts, regional structures that reward local performance over enterprise value, disagreement about ownership or a history in which information has been used politically. A common customer relationship management system can address the first problem. It cannot resolve the others unless leadership addresses them as well.
The same pattern can be found in reporting. An organisation may invest in analytics because managers complain that decision-making is too slow. Better data can certainly help, but slow decisions may have little to do with information. Multiple approval layers, risk avoidance, poorly defined decision rights or a culture in which managers hesitate to act without senior endorsement can persist after the new system is introduced. The organisation then possesses faster information inside an unchanged decision structure.
This is one reason technically competent programmes can produce disappointing outcomes. The software works. Data migrates. Employees complete their training. Yet managers continue to request the spreadsheet they previously trusted, teams develop workarounds, and informal channels retain more influence than the official system. What looks like poor adoption may actually be evidence that the organisation changed its technology without changing the conditions that gave the old practices their value.
Technology therefore deserves to be examined not simply as a tool introduced into an organisation, but as an intervention in an existing system of relationships, incentives and authority. The stronger the technology becomes, the more consequential that intervention can be.
What Has Changed Since 2004, and What Has Not
Bennet Lientz and Kathryn Rea published Breakthrough IT Change Management in 2004. Some of its technological context inevitably belongs to its period. The book discusses areas such as e-business that occupied a different position in management thinking at the beginning of this century. Since then, cloud computing, software-as-a-service, mobile platforms, advanced analytics and artificial intelligence have changed both the capabilities available to organisations and the speed with which some technologies can be deployed.
What has aged more slowly is the organisational problem described underneath them. Lientz and Rea begin their approach with the existing culture and organisation, then move through resistance, change objectives, implementation, measurement, momentum and the prevention of reversion. Technology appears within that wider system rather than being treated as an isolated installation problem.
More recent academic work has reinforced the systemic interpretation. Hanelt, Bohnsack, Marz and Antunes Marante reviewed 279 studies of digital transformation and concluded that the phenomenon involves more than the impact of individual technologies. Their analysis describes movement towards organisational designs capable of continuing adaptation and identifies perspectives ranging from technology impact to systemic change and broader organisational co-evolution.
There is an important implication here. Management terminology evolves more quickly than many management problems. What was once discussed as IT change became digital transformation; today, many organisations are framing a similar discussion around artificial intelligence. The technologies are not equivalent, and it would be a mistake to treat them as such. AI raises questions about judgement and knowledge that a conventional enterprise resource planning implementation does not. Nevertheless, each generation of technology encounters the organisation that already exists.
That organisation has history. It has formal structures and informal ones, accumulated compromises, trusted people, contested boundaries and routines whose original purpose may have been forgotten. Some inefficiencies are technical. Others are the residue of decisions that were once rational in a different environment.
A new system enters all of this. It follows that a technology programme cannot be understood only by studying the technology being introduced. Leaders also need to understand what the existing organisation is likely to preserve.
Technology Changes Authority as Well as Process
The most significant effects of technology are sometimes described in the language of process improvement when they are actually changes in organisational power. A common information system does more than make data easier to access. It changes who possesses information, who can compare performance and who can challenge another person's interpretation of events.
Consider introducing a common commercial platform across previously independent business units. Headquarters may see better visibility, improved forecasting and a more complete understanding of strategic customers. Local managers may experience the same system as the removal of informational discretion. Neither description is necessarily wrong. They reflect different positions inside the same organisational change.
Automation introduces a similar tension. A process can become more efficient while reducing the authority attached to a particular role. Work that once required experience may become partially standardised. Activities that justified managerial supervision may disappear. The economic case may be convincing, but the human consequences do not vanish because they were absent from the business case.
Artificial intelligence further complicates this issue because it can move technology into areas previously associated with professional judgement. When AI contributes to an analysis, recommendation or customer interaction, management must determine more than whether the output is technically useful. It must decide who has authority to rely on the output, who is expected to challenge it and where accountability sits when human and machine contributions are intertwined.
The distinction matters because responsibility cannot simply be automated alongside the task. A professional may remain accountable for an outcome while having less control over the process that produced it. If organisations fail to make this relationship explicit, they can create an uncomfortable asymmetry: technology receives increasing influence while human accountability remains unchanged.
For senior leaders, these questions are organisational design questions. The programme may originate in technology, but decisions about authority, transparency and responsibility belong to management.
This also explains why communication alone cannot solve every adoption problem. A manager who is losing discretion does not necessarily oppose a new system because its advantages have been poorly explained. An experienced employee whose expertise is being codified may understand the business rationale perfectly well. The difficulty lies in what the change means for their role.
Leadership still has to make difficult choices. Not every role should be preserved, and not every form of discretion creates value. The requirement is more demanding: leaders should understand what they are changing rather than describing a redistribution of authority as a communications issue.
Resistance Can Be Irrational, Rational or Informative
Change-management literature has long examined resistance, but the term can become too broad to be useful. It can describe fear of unfamiliar technology, the protection of status, scepticism stemming from previous failed programmes, legitimate concerns about customers, or simply disagreement with the assumptions behind the change. Treating all of these reactions as the same problem encourages leaders to focus on overcoming resistance instead of understanding it.
Employee research offers a more nuanced picture. Klein, Spieth and Söllner's 2024 study on employee acceptance of digital transformation strategies found that employee responses were influenced by their understanding of the expected scope and consequences of the change. Their work contributes an employee-level perspective to a field that has often emphasised top-down management capabilities.
This should not be interpreted as an argument that employees must agree before change can proceed. Organisations would become paralysed if every objection acquired veto power. Some opposition does protect familiar routines long after those routines have stopped creating sufficient value. Yet dismissing resistance too quickly carries a different risk: the organisation may remove precisely the operating knowledge needed to make the new system work.
People close to customers and daily operations often understand exceptions that appear irrational from the centre. A process that looks unnecessarily complicated may reflect a regulatory requirement, contractual obligation or customer expectation not visible in the original design. Equally, claims of local uniqueness can become a convenient defence of processes that no longer have a commercial justification.
International organisations encounter this tension particularly clearly. A central platform often seeks common processes across businesses operating in different institutional and customer environments. The objective of standardisation may be sound, yet the design can carry assumptions about hierarchy, approval, documentation or customer interaction that do not translate well.
The executive responsibility is therefore to distinguish useful variation from inherited complexity. That judgement requires more than listening sympathetically or enforcing compliance. It requires understanding where value is created.
Resistance, viewed this way, can contain three different messages. The organisation may be protecting the past. People may be responding rationally to a change in their own position. Or the proposed design may genuinely be weaker than its sponsors recognise. Mature change leadership has to determine which message it is hearing.
The Business Case Is Realised After Implementation
Technology programmes also create a measurement problem. Implementation expenditure is visible long before organisational value is.
A board can monitor whether the programme remains within budget, whether milestones have been achieved and whether users have migrated. These are necessary measures, but they primarily reveal whether the project has been delivered. They say much less about whether the original economic assumptions have become true.
The distinction is important because most business cases depend on behavioural consequences. Automation is valuable because work changes. Better data is valuable because decisions change. A CRM system is valuable because commercial behaviour changes. Collaboration technology is valuable because information and expertise move differently through the organisation.
McKinsey's research into digital transformation has identified associations between successful transformations and factors including leadership, capability building, employee involvement, changed ways of working and the integration of digital tools into everyday operations. Its survey findings should be treated with the usual caution applied to self-reported transformation studies, but the underlying distinction is useful: deployment and organisational performance are not the same outcome.
Consider an automation programme that promises significant labour savings. The technology may remove thousands of hours of manual activity, exactly as expected. Yet if staffing, workloads, organisational layers and approval processes remain unchanged, the saving may never appear as lower cost. The released capacity could still create value elsewhere, but that is a different economic outcome and should be recognised as such.
The same applies to decision quality. Giving managers better information has limited value if nobody has clarified who can act on it. Faster reporting inside a slow governance structure can simply allow the organisation to observe its problems more efficiently.
This gap between technological capability and economic realisation deserves greater board attention because it is where accountability often becomes blurred. Technology teams may reasonably argue that they delivered the system promised to them. Business leaders may respond that the benefits were never realised. Both can be correct.
A serious business case should therefore describe not only what the technology will do, but which organisational behaviour must change for the financial or strategic value to materialise. It should also identify who owns that change after implementation.
The economics of transformation often begin where the project plan ends.
Standardisation Is an Economic Choice, Not a Technical Virtue
Many large technology initiatives contain an implicit promise of standardisation. Common platforms can reduce duplication, improve data quality, simplify support and give leadership a more coherent view across an enterprise. In organisations that have accumulated different systems through growth or acquisition, the economic case can be substantial.
The difficulty is that standardisation is sometimes treated as inherently superior to variation. It is not. Its value depends on what is being standardised and why.
A common financial definition may increase transparency without damaging customer value. A standard cybersecurity control can reduce risk across the enterprise. A universal commercial process, by contrast, may become more problematic if customers, regulations or routes to market genuinely differ.
The trade-off is therefore between the economics of commonality and the economics of responsiveness. Every local exception increases complexity. Removing every local exception can make the organisation easier to manage internally but less responsive externally.
This is also an organisational power question. Standardisation often shifts discretion from operating units to a central function because someone must determine the common process. That can improve discipline and visibility. It can also weaken local judgement if central designers do not understand the environment in which the process will operate.
Neither decentralisation nor standardisation deserves automatic preference. Mature organisations need enough commonality to behave like one enterprise and enough variation to respond intelligently where conditions genuinely differ.
Technology makes this choice unavoidable because systems encode decisions that organisations could previously leave ambiguous. Two divisions can interpret the same policy differently for years. A common platform eventually requires somebody to decide which interpretation becomes the process.
Many difficult technology debates are therefore management disagreements expressed through system design.
Not Every Technology Project Is a Transformation
There is a credible argument against expanding every technology programme into a broad organisational-change exercise. Organisations can overmanage change. Routine upgrades can acquire transformation offices, workshops and communication campaigns that add cost while frustrating people who simply need a better system.
That criticism is justified. Mature organisations should be able to modernise infrastructure and improve well-understood processes without treating every implementation as a cultural intervention.
The distinction should depend on organisational consequence. If a technology changes the tool while leaving responsibilities, decision rights, customer interactions and economic logic substantially intact, normal implementation disciplines may be enough. If it changes who performs the work, where information sits, who possesses authority, what expertise remains valuable or how customers experience the organisation, the change has moved beyond technology.
This matters because both errors are expensive. Underestimating organisational consequences produces systems that employees circumvent and benefits that remain theoretical. Overestimating them creates transformation bureaucracy, slows useful improvement and contributes to fatigue.
The executive task is calibration.
Technology teams need room to implement technology. Business leaders need to recognise when a technology decision has become an operating-model decision. Change management adds value when it addresses the organisational consequences of change; it adds far less when it becomes ceremony attached to every system implementation.
This distinction is especially important now that AI is attracting transformation language across almost every function. Some AI applications will significantly alter professional work and organisational authority. Others will simply make a familiar task faster. Senior leaders should resist both the temptation to dismiss the former as another software implementation and the temptation to elevate the latter into strategic reinvention.
What Senior Leaders Should Consider
A useful starting point is to redefine what completion means. Go-live is an operational milestone, not necessarily the end of transformation. Before approving a significant technology programme, leaders should be able to describe what the organisation is expected to do differently after implementation and where the resulting value should become visible. If those connections cannot be articulated, the business case probably contains assumptions that have not yet been examined.
Decision rights also deserve attention earlier than they often receive it. Leaders should identify where a system will increase transparency, remove discretion, centralise authority, decentralise information or introduce automated judgement. These consequences should be discussed as management choices before they emerge as political conflicts during implementation.
Measurement should then move beyond adoption. Training completion, user activity and migration percentages help programme teams understand whether implementation is progressing. Senior management should connect them to measures that matter economically: productivity, customer value, cost, working capital, revenue quality, decision speed, risk or organisational capability.
Finally, organisations should decide what they are prepared to stop. New technology layered over old reporting, old approvals, duplicate data and parallel processes increases complexity rather than reducing it. Reversion is rarely prevented by communication alone. It is prevented when the old system loses its organisational legitimacy: leaders stop asking for the old report, incentives reinforce the new process, and workarounds are no longer tolerated simply because they are familiar.
Questions for the Boardroom
- What must change within the organisation for the economic assumptions behind this technology investment to hold true?
- Which decisions about authority, accountability or professional judgement are currently being treated as technical implementation details?
- Where does local variation genuinely protect customer or regulatory value, and where does it merely preserve organisational history?
- What existing activity, report, approval or process will disappear when the new system becomes operational?
- Twelve months after implementation, what evidence would demonstrate that business performance changed rather than simply technology usage?
The Organisation Is Part of the Technology
The technological distance between 2004 and today is considerable. The organisational distance is less dramatic.
Lientz and Rea were writing before cloud platforms became commonplace and long before generative AI entered ordinary management conversations. Yet their decision to begin technology change with culture, organisation, resistance and implementation discipline remains instructive. The enduring issue was never a particular generation of software. It was the relationship between the system being introduced and the institution expected to use it.
New technology often reveals that institution more clearly than management expects. Poor data can expose weak accountability. Attempts at standardisation can reveal unresolved tension between central and local authority. Automation can expose work whose value has never been examined carefully. AI can force organisations to define where judgement ends, and accountability begins.
These are useful revelations, though not always comfortable. They remind leaders that an organisation is more than a collection of processes waiting to be optimised. It is also an accumulated system of knowledge, relationships, incentives, responsibilities and memory. Some of that inheritance represents unnecessary friction. Some of it represents capabilities that would be expensive to rediscover once they are removed.
The deeper challenge of technology transformation is therefore one of judgement. Leadership has to decide which parts of the existing organisational technology should be replaced, which should be strengthened, and which should be deliberately left human.
That judgement cannot be delegated to the system.
Technology may increasingly shape how an organisation sees, decides and acts, but the responsibility for deciding what kind of organisation emerges remains with its leaders. Sustainable change begins when that responsibility is recognised before implementation rather than after the expected benefits fail to appear.
References
- Hanelt, A., Bohnsack, R., Marz, D. and Antunes Marante, C. (2021). ‘A Systematic Review of the Literature on Digital Transformation: Insights and Implications for Strategy and Organizational Change’. Journal of Management Studies, 58(5), 1159–1197.
- Klein, S. P., Spieth, P. and Söllner, M. (2024). ‘Employee Acceptance of Digital Transformation Strategies: A Paradox Perspective’. Journal of Product Innovation Management, 41(5), 999–1021.
- Lientz, B. P. and Rea, K. P. (2004). Breakthrough IT Change Management. 1st edition. Routledge.
- McKinsey & Company (2018). ‘Unlocking Success in Digital Transformations’.
About the Author
Andy Demir is an international commercial and business leader with more than two decades of experience across complex B2B and industrial markets. He writes about executive leadership, strategy, organisational transformation, commercial performance, international business and the changing world of work, combining research with lessons drawn from operating across industries, markets and cultures.
