Well-geared IT analytics are key to ensuring project success for companies, says study

Only 20% of projects are recognized as fully successful
Qualitative hunches are too often relied on, and are misleading
IT analytics provide an in-depth quantitative analysis, highlighting gaps and simplifying problem solving

Digitizing the business value chain is critical for competitiveness in today’s global interconnected economy. However, getting to that digital state is challenging with more than 80% of current IT-enabled programs either not  delivering the expected transformation or exceeding the allocated budget, says a Strategy& study.

According to Strategy&, most companies when carrying out projects tend to rely on traditional project management office (PMO) practices, which focus on lagging indicators instead of predictive IT analytics. PMOs merely provide a backward view of a project’s progress, and are not set-up to spot problems before they become full-fledged crises that can disrupt schedule and budget.

Most companies track massive amounts of data which is usually presented in hundreds of dashboards. Too often, IT departments spend time and effort focusing on maximising the dashboard technology and not analysing the findings. As a result, the IT analytics process is essentially broken with large volumes of data floating around – providing no clear insights. This eventually leads to disengagement among stakeholders and blinds the leadership to impending issues.

Samer Bohsali, a partner with Strategy& and the leader of the firm’s Digital Business and Technology practice and Digitization platform in the Middle East, said: “Most companies already have the data that reveals problems early in the project’s life cycle, which could be a helpful warning sign in implementing corrective measures that are less expensive. However, companies fail to track and interpret the right data, and turn their conclusions into actionable business decisions which are necessary to guide the project, keep it on track and within budget. As a result, the project becomes costly, cumbersome, and efficiency is heavily compromised.”

The Strategy& study suggests three corrective steps to fix a broken IT analytics process which includes identifying and tracking the right data, empowering the project team and finally, converting insights into business decisions.

  1. Identifying and tracking the right data According to the study, to move the focus from lagging metrics to predictive analytics, organizations must identify, collect and use the appropriate level of data throughout the entire life cycle of the program. In order to make the most of the benefits offered by in-depth analytics, companies need to dig below the qualitative hunches of managers monitoring dashboards, to more quantitative insights based on analytics. By relying on quantitative scores, teams are able to spot risks early on, and can estimate downstream implications. Corrective actions can therefore be taken when necessary, and both costs and time can be saved. In order to ensure that the right metrics are in place, a comprehensive IT analytics framework should be established prior to the program execution to ensure that the various sources of information are accessible.
  2. Empowering the team The study highlights the need to have the right people looking at the data. This involves training and encouraging project managers who are responsible for creating, presenting and monitoring executive scorecards. AbdulKader Lamaa, a principal with Strategy& and a member of the firm’s digital business and technology practice leadership team, said: “Often, these project managers do not have the full functional or technical knowledge to get to the root cause of a metric. Aside from daily involvement of project managers, System Integrators (SIs) that are responsible for the technology implementation should be incentivized to establish the IT analytics process and transfer the ownership and knowledge to the client team.”
  3. Turning insights into business decisions Once the right data is tracked and interpreted, it should be passed to the right people who can make actionable decisions. This requires clear lines of communication, decisions rights, and accountability within and across businesses. Analytics can help create a “single version of the truth” and accelerate decision-making by forcing consensus through data, instead of subjective opinions, especially in a multi-stakeholder or siloed organization.

However, the study reveals that unfortunately, the prevailing culture and governance structure in most organisations in the Middle East hamper this process.  Instead of presenting executives with fact-driven data analyses to prove or disprove hypotheses related to program performance challenges, most people tend to get ahead through relationships and political alliances. As a result, problems often remain hidden until they blow up and become huge, expensive and time consuming distractions.

Sevag Papazian, a principal with Strategy& and a member of the firm’s digital business and technology practice leadership team, said: “Good governance depends not just on setting up a sturdy structure but also an enduring one that can be sustained during the entire length of the program while leveraging the IT analytics process.”

A well-geared transformational analytics framework is key to driving a successful program

“If a well-defined governance structure is in place, a skilled team is established, and the right data is tracked and analysed, a company has succeeded in creating a well-geared IT analytics process which recognises early signs of troubles, enables continuous monitoring and improvisation and identifies potential constraints and bottlenecks. Ultimately, it is these capabilities that enable companies to implement transformational IT projects on time,  which will then help them towards boosting the ROI and differentiating from competition, ” concluded Papazian.
In addition, the IT analytics framework also enables an objective data-driven measurement of the transformation’s impact on the organization and corresponding benefits, to assess whether the initial program objectives have been met.