Data Scientist or Data Science Team
One of the buzz words for 2013 was data scientist. An elusive and brilliant data analyst with the ability to effortlessly navigate business culture and politics while employing data science to generate business value from a sea of unstructured data. Small and midsize businesses were as likely to find a data scientist to hire as to find a unicorn waiting at the front door. According to Ted Cuzzillo in an article on Information Management, not being able to find one data scientist should not be surprising because the required skill set is beyond what any single person can possess. Data science is a team sport and requires varying skills that fit a business's needs and structure. There is no single hire who will move the business to the front edge of business intelligence.
Know the Sport
Business analytics, like all IT solutions, is meant to solve problems for the business. The problem requires definition before any decisions about a desired skill set, the proper technology or manageable business structure can be made. An initial assessment of business data, current employee skills and existing analytics technology is necessary to identify what gaps will require committed resources. Business structure and culture also influence whether resources will be deployed and integrated with specific business units or as a shared service to the entire company.
Build the Team
Midsize businesses typically maintain a closer relationship between business and IT units, which allows them to follow an integrated model for developing business intelligence capabilities. Developing business intelligence in this case depends on key employees having the ability to bridge business understanding and technical skills. Employees with technical abilities and business savvy IT professionals are both candidates for the pivotal roles between the business and IT knowledge domains. A trust for data-centric decision making within each business unit may prepare these employees to use data tools as they are made available.
Technology choices for managing data and serving visualizations determine whether IT employees require additional training or should have their skill set augmented with new hires. However, limited availability of necessary skills in the external hiring pools can encourage internal skills development. Redeployment of existing employees to fill expanding data roles can be assisted by outsourcing basic IT operations to cloud services partners. IT leaders who are creative when shifting personnel resources will succeed in building internally skilled data science teams.
Equip for Success
Data science across a business is not entirely reliant on employee skills; technology that enables is also needed to handle operationalized analytics. A successful business intelligence program discovers new information in the data and moves toward automated processing. Midsize businesses that are sensitive to costs recognize the need to keep high-priced data science talent focused on difficult problems. Business analytics visualization technology in the hands of business end users can accomplish this goal.
When data analytics has been established for a business, human experts can be assisted with machine learning and data discovery algorithms. For a business to be able to trust insights from machines, it requires a data-driven culture. The jump to advanced tools is tempting but wastes resources if the team is not ready to work at an advanced level.
This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. Like us on Facebook. Follow us on Twitter.