Your Team Doesn’t Need a Data Scientist for Simple Analytics

Data analytics is a powerful and promising source of competitive advantage. But organizations are often hobbled by the lack of the requisite skills in the marketplace. To cope with the shortfall in market supply, companies need to better leverage their existing talent. One strategy is to take the team approach to cross-pollinate and commingle the required skillsets, bringing together a diversity of skills and backgrounds from within your organization. Seek individuals who are innovative, frugal, and creative, who produce maximum results with minimal resources. This combination of creativity and curiosity is difficult to teach, but essential to effective analytics.

Arthur Nielsen, market research pioneer and founder of the Nielsen Corporation, once said, “The price of light is less than the cost of darkness.” As data proliferates across the enterprise, this observation by Nielsen is rendered even more relevant, because data represents the unlit fuel that has the potential to light the darkness, but which often lacks the spark of analytics that enables us to see.

The mission of enabling data analytics in today’s enterprise is hobbled by the lack of the requisite skills in the marketplace, including: advanced statistics/mathematics, new analytics methodologies, advanced systems analysis, business fundamentals, regulatory and legal understanding, and general IT technical and data architecture skills.

To cope with the shortfall in market supply, companies need to better leverage their existing talent. Having founded a data management company and worked with hundreds of organizations over the past 20 years to execute their information management and analytics initiatives, I’ve found the groups that are able to successfully utilize their company’s analytics technologies often take the following approaches:

Build a team. One strategy is to take the team approach to cross-pollinate and commingle the required skillsets; bringing together a diversity of skills and backgrounds from within your organization to achieve a common goal is a highly effectivemethod.

Start by identifying the characteristics and needs of your organization’s environment. For example, highly complex product and service environments will require domain experts or subject matter experts. Simpler product environments will require experts in operations, logistics, and supply chain. Formulate teams that reflect your particular needs, and consciously design your team’s framework and composition to transfer skills across functional or organizational boundaries.

Find the supporting players. I suggest going outside your department in order to lay the foundation for functional analytics initiatives. It will be productive to search across your organization for a few relevant skillsets that will enable your team to make use of the data available:

Seek creativity and curiosity. The foregoing is a good start at convening a team of diverse skill sets in order to enable, if you will, “analytics for the rest of us.” However, there is one set of essential traits to be found in your team that will drive the initiative.