McKinsey says there will be a shortage of data skills in 2018. Mckinsey predicts a shortfall in meeting the demand for 1.5 Million Data Savvy Managers. Savvy managers can make use of data on the execution side, putting insight into context and making things happen.

A major hurdle to iterating and improving strategic data driven decision making is people. Data analytics is pretty straight forward; i.e. math is just that, math. It's people (humans) that is the problem. Which means people (could that be you?) are the solution. Data science relies heavily on statistical computing. Scripts and math. Algorithms. If (1) you start with good data and (2) you have a competent data scientist conduct and interpret the analysis, you still need (3) to put those results into context; make something happen. Someone has to do! Teams (doers) need to execute on insights.

Here are six skills tech startups are looking for in a data savvy manager:

Listen. Understand the problems your team, senior, & mid-level managers are facing.

Ask great questions. Frame the problem into a set of questions that, if answered, direct action. Understand (& communicate) that decisions must be made once these questions are answered.

Understand data science. Take a survey level course on data science. LinkedIn Learning offers a course that you can get through in an afternoon. When you understand the process you can ask actionable questions that lend themselves to be answered with a data model.

Evaluate alternatives. Data often suggests multiple approaches; assemble the right team that can prioritize them.

Acknowledge and mitigate bias. Team members have (and use) inherent bias. Teams that manage GroupThink will naturally make better evaluations.

Catalyze change. Communicate and empower decisions throughout the organization. Building the architecture need for changes to take place.

These six skills are crucial to developing processes that:

(1) generate meaningful questions

(2) pose those questions effectively

(3) build understanding around data driven decisions

(4) create a culture that can implement those decisions.

Data Science requires rare (specialist) qualities:

(1) an ability to take unstructured data and find order, meaning, and value.

(2) Deep analytical talent.

​Data Savvy doesn't.

To be a generalist, a data savvy manager, doesn’t. Data savvy doesn't require you to be a math expert,

learn more @


Data Savvy doesn't require you be a #machineLearning #dataScience expert. Turn your data dump into Actionable insight @