For even the most competent teams, data can be a struggle.
In today’s world, we collect massive amounts of information and hope to consolidate, interpret and leverage it to better meet our business goals. Often times, data is also sought out to identify what is hindering achievement of targets, whether customer-driven, such as a loss of revenue, or internally focused, like high staff turnover or leadership change. However, even with seemingly endless amounts of data at our fingertips, we often do not know where to begin or how to use data to drive improvement.
It is in this grey area, even with a dedicated data science staff, that the process quickly becomes unwieldly. Whether it’s the wrong questions driving analyses or errored data clean-up efforts leading to incorrect conclusions, problems with managing and interpreting data contribute to a team’s lack of effectiveness and efficiency, as well as increased levels of frustration among staff. Overall, it is these complications that contribute to the fact that only 13% of data and analytics projects reach completion, and of those that do, only 8% of leadership report being completely satisfied with the outcome.
But data doesn’t need to be unmanageable and the outcomes don’t need to be unsatisfactory. In fact, using Quisitive’s approach—which assists businesses with digital transformation by helping to create viable, valuable solutions to company or customer problems—leaders may quickly realize that data is an asset that has value. Their method of working with clients takes place in three distinct phases, including making a case for change, ideation of that transformation, and finally, acting upon it. To start this first step in Quisitive’s approach—making the case for change—a clear definition of a problem is needed, not only to understand the issue being faced, but to also enact solutions that drive the second phases of ideation and action. It is here that quality data is needed.
Quisitive provides thought leadership, expertise and guidance to turn data from a cumbersome liability into something relevant, tangible and accessible for identifying company problems and meeting business goals that drive maximum return on investment. Managing these efforts is Quisitive’s data science team, led by James Roberts, chief data scientist, and Shannon Ragland, data science strategist.
Combined, James and Shannon—both formally trained in applied statistics doctoral programs at the University of Texas at Austin and Arizona State University, respectively—have over 25 years of experience in academia and business. In addition to publishing dozens of peer-reviewed empirical research studies while teaching in higher education, they have over 17 years of consulting experience working for small start-ups as well as large, international corporations. Their clients have spanned across a broad range of industries, including retail/e-commerce, higher education, financial services, entertainment, government, biotechnology and petroleum. It is James and Shannon’s combined, expansive knowledge about how to manage and analyze data that make them an asset to advancing Quisitive clients’ business goals that achieve sizeable returns on investment.
In upcoming posts in this series of blogs highlighting Quisitive’s Data as an Asset solutions, James and Shannon will be lending this expertise so that your business can also have a partner in better managing its data. Their next post will examine Quisitive’s Six Keys to a Successful Data Initiative, which details the critical steps for establishing a successful foundation for identifying and solving business problems.