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How to use data analytics to improve project outcomes

Moira Alexander | March 21, 2017
Worldwide revenues for big data and business analytics is expected to grow to more than US$187 billion by 2019 and the project management industry is projected to hit US$5.81 trillion by 2020. Here is how some organisations are leveraging data analytics to improve their project performance.

He suggests answering this question: "How do we know we are doing what we intended to do?" and "How do we know if what we did worked?" Jason elaborates further on their methods for measuring implementation fidelity and efficacy.

For implementation fidelity, WGU has used many methods, ranging from analyzing log data of student sessions with electronic learning materials to having faculty use hashtag notations in the student notes.

For efficacy, "our bias is to use randomized control trials, but we also use quasi-experimental methods. The most important data is to have a clearly defined outcome variable that can be reliably measured. Western Governors University (WGU) has a competitive advantage with outcome variables compared to traditional higher education institutions. At WGU, all our assessments are centrally developed to rigorous standards. This system of assessment produces much more reliable data than having faculty individually assigning letter grades."

He also describes another unique aspect of data at WGU - its "domain taxonomy or hierarchy of learning outcomes mapped to learning materials and assessments. Student learning behavior can be mapped between the electronic course materials and assessment. Formative assessment data is more predictive of success on the high stakes assessment than simple pageviews."

To make the best decisions, companies need to be able to extract precise and relevant information from the data available. Absent this, raw data, no matter the quantity, serves no purpose. Ultimately, companies are seeking the type of information that tells them what their customers want most and is critical for guidance on project initiatives, direction, execution, and metrics.


How are companies using data analytics to improve project outcomes?

No matter what the industry, from technology to sports or education, data analytics has become an essential tool for enabling successful project outcomes and ultimately company-wide strategy.

"We use data analytics to examine almost everything about our platform, including how many times our users request customer support, says Jonathan Rodriguez, Founder, and C.E.O. at BitMar Networks. "The first thing that we realized was the more solutions we offered before our users even requested them, the less our users requested customer service".

He has confidence that by implementing data analytics, BitMar found a completely new approach to recruiting. Data told BitMar that "your users do not need your tech support, they prefer to talk to one another, instead. So, provide that functionality and let them be." This highlighted the need for the company to hire community enthusiasts instead of customer service staff.

BitMar embarked on a project to develop a self-help platform for customers. "Who would have thought that we would have been able to provide a platform in which the users get to help themselves, at virtually zero cost on our end?," says Rodriguez. Data analytics not only helped BitMar zoom in on the types of projects they should be taking on, it also identified opportunities within projects to improve customer satisfaction and still reduce internal costs.


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