Why do large and complex ICT and digital transformations fail?
October 31, 2018
Framework for managing success and failure factors
The well-known fact is that a majority of complex ICT and digital transformations fail in reaching their corporate goals, are delivered late or are over budget.
Midagon asked two distinguished Aalto University professors, Matti Rossi and Kari Smolander, to identify the factors behind success and failure, based on scientific research. Matti and Kari reviewed all of the relevant academic literature that was published during the past 20 years.
Based on their critical review, Midagon summarized the main findings. Our recipe for success is found in the new Midagon White Paper which can be accessed here.
Critical Success and Critical Failure Factors
An understanding of Critical Success Factors (CSF) and Critical Failure Factors (CFF) is vital. The complete list of Critical Success and Critical Failure Factors is presented in the white paper. Table 1 summarizes the top 5 factors in each category.
The complete list of Critical Success and Failure Factors comprises a total of 15 factors in both categories. In a project, the absence of success factors or the presence of any of these failure factors almost certainly leads to failure.
When all of the success factors are present, and all failure factors removed, the likelihood of success is less than 50%.
Choosing the right project methodology
During the past 20 years, there has been an emphasis on developing new project management methodologies to decrease the risk of failure. The overall tendency has been to move from waterfall approaches to SCRUM/ Agile, large scale agile (e.g. SAFe) or to Continuous Development and Delivery (DevOps).
In the rapidly changing business environment, according to research, Agile and other new methodologies appear to have a positive impact on the probability of success. The new methodologies have definitely improved employee satisfaction.
The right choice of project methodology is, therefore, important. However, it only provides part of the solution. In our view, guaranteeing success in complex ICT and digital transformations requires a comprehensive approach. This is because critical success and failure factors are largely universal and independent of the chosen methodology.
Improving the probability of success
According to the research, in failed ERP projects, the main problem is associated with leadership (42% of the cases), followed by organizational and culture (27%) and human and people (23%).
In our view, in leading complex ICT and digital transformations, the key ingredients of success revolve around the following three elements (in the order of importance):
- Leadership
- Addressing Critical Success and Failure Factors (CSF and CFF)
- The right choice of project methodology
Midagon has developed an assessment tool, which utilizes the Critical Success and Failure factors. We propose that each complex ICT and digital transformation project should be benchmarked against these factors, in order to obtain a score that predicts the likelihood of success or failure.
Success and failure factors should be embedded into the project methodology and considered in each lifecycle stage of the project. Continuous monitoring of the maturity is a must.
The project methodology should be chosen, based on the organization’s capability and the type of project challenge. Especially in complex and geographically distributed ICT and digitalization projects, we recommend using hybrid approaches that combine elements from waterfall and agile. Reacting to change is more important than following a plan.
Finally, strong, hands-on leadership is vital. Success depends on people. We seldom see great results, without inspiring leadership and without a competent and committed team.
In leading complex ICT and digital transformations, the objective should be to move from reactive problem-solving to predictive leadership and execution. When we know the Critical Success and Failure factors, we can start creating an algorithm of success. Backed by experience and data, we will ultimately start to improve the probability of success.
Ilkka Töyrylä ja Lauri Eskola
