Years ago, I lead the creation of an Anti-Money Laundering (AML) Model for a compliance investigative team. The model did a great job identifying brokers and customers who were deemed anomalous- math nerd for probably committing fraud, but we couldn’t explicitly prove it. Upon delivering the model results to our investigative team, the users dismissed it as unhelpful because it didn’t provide them with an explicit definition for why it was anomalous. As analysts, we could offer insights into why we thought an individual instance was being identified, but it could not scale to each flagged policy. The pilot was shut down for lack of adoption; not because the model didn’t work, but because it didn’t meet the expectations of the users.
Much like the AML model, digital transformations are big targets for needing to manage the expectations game. While much focus is often placed on strategy and execution, the gap between expectations and reality can distort the impact of the program. This can lead to a feeling of failure, even when the implementation has been successful. To underscore this point, let's explore the importance of managing expectations in the context of digital transformations.
One of the harsh realities of digital transformations is that they frequently experience delays and cost overruns. It is estimated that approximately 70% of projects experience delays; if your transformation has four projects, there is a 99% chance that at least one project will experience delays. While the initial expectations might be for a swift, cost-effective transition, several factors contribute to these disconnects with reality.
Underestimation of Complexity: Digital transformations are inherently complex, involving changes in technology, processes, and, at times, organizational culture. Stakeholders may not fully comprehend the intricacies and potential complications, leading to overly optimistic expectations about the ease and speed of the transformation.
Inadequate Communication: Effective communication is crucial to align expectations with reality. When stakeholders are not kept informed about progress, potential setbacks, or realistic timelines, they may form unrealistic perceptions of the project's trajectory.
Resource Constraints: Limited resources in terms of budget, personnel, or time can affect the pace and extent of the transformation. Unrealistic expectations may arise when stakeholders assume that the project can be completed more quickly or with fewer resources than is realistically possible.
According to an Experian study, inaccurate data impacts the bottom line in 88% of companies. In another study, Gartner estimates the impact is about $15 million dollars a year. Data quality is a large scale that is usually underestimated and reported, causing significant problems with transformative efforts. Expectations about data quality may not align with the reality of complex data ecosystems. Three common areas where data can be negatively impacted are:
Process: If data processes are not well-defined and replicated throughout the organization, the usage of fields can vary, impacting data quality.
Controls: Lack of rules and controls for data input can lead to poor data quality as inconsistencies creep into the dataset.
Complex Business Rules: Overreliance on complex business rules can lead to technical debt, making it challenging to maintain high data quality standards.
Many organizations underestimate the importance of change management in digital transformation; one study found 75% of companies struggle with it. Digital champions often belive that everyone will see how amazing everything works, and they will fall in line with their leadership. Senior leaders, however, may also have concerns about the digital transformation and may not fully support the initiative. Furthermore, most, it not all, employees will need to gain new skills to perform their roles. The leadership is not usually qualified to teach and mentor the employees in their new roles.
The impact of digital transformation on an organization's operations and productivity is a critical consideration. Expecting immediate improvements can often be unrealistic.
Productivity Decline: As the organization and its employees adjust to new processes and technologies, there may be a temporary decline in productivity, as explained by the Solow Paradox experienced in the 1970s.
Customer Learning Curve: Customers also need time to adapt and benefit from new systems and services, leading to a potential decline in customer productivity.
Managing expectations is an essential component of any digital transformation initiative. The gap between the slow progress of change and the high hope for immediate impact is a significant challenge that organizations must address. A thorough understanding of the complexities and potential setbacks in digital transformation, coupled with effective communication, is key to bridging this gap and ensuring that stakeholders have realistic expectations.
In the ever-evolving landscape of digital transformation, successful projects are not only about implementing the latest technologies but also about managing the human side of change. Organizations must recognize that managing expectations is not just about delivering the expected results but also about fostering a sense of trust and alignment among stakeholders, ultimately leading to a more successful and harmonious transformation journey.
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