A list of the important skills for data scientists needs to include a structured approach for incorporating business systems thinking in organizations. This need is addressed through the Integrated Enterprise Excellence (IEE) Business Management System.
The IEE system provides a basic data science framework. With an IEE structured approach, big data and other analyses can be more effective relative to fulfilling business needs. The described data scientist execution roadmap provides a vehicle thought process for problem solving. In addition, the systems-thinking methodology of the IEE roadmap is a presentation methodology that is useful for not only data scientists but c-suite executives and others as well.
This IEE data science presentation methodology, with its predictive performance measures, offers a means where data science is available for everyone in an easy-to-understand format. This click-of-the-mouse access to information can be useful for both strategic and day-to-day decision making.
IEE addresses a means to address the business management and data scientist issues that are described in a 1-minute video:
What is a Data Scientist and data science?
Wikipedia describes Data Science as the utilization of data to gain knowledge. Data science, which is executed by a Data Scientist, involves many fields including mathematics, probability models, and statistical learning. Data Science can involve big data but is not to have a big data application restriction.
Good data scientists are not restricted to business problem resolution but also selecting the most organizational problems to solve. Simply teaching data science tools without a structure for implementation can lead to much confusion and execution inconsistencies.
The focus of this blog will not be the tools that programmers use to gain data access but instead:
- A framework for the business to operate within so that data science is used structurally to monitor and benefit the business as a whole
- A roadmap to structurally evaluate process data relative to make an improvement
Data Scientist Execution Roadmap
The Integrated Enterprise Excellence (IEE) system provides data scientists both an operational framework and roadmap for structurally addressing data science efforts. The IEE system is a 9-step methodology:
Discussion about how this 9-step system addresses current business-management system issues along with the execution of each step is shown at: Enhanced Business Management System. One thing that is highlighted in this link is the IEE value chain in step 2, which describes what an organization does and how it measures what it does using a predictive performance metric. This IEE value chain provides data science information that can be used strategically and at the local process-execution level.
To reiterate, the IEE system provides a framework for the business to operate within so that data science is used structurally to monitor and benefit the business as a whole. The IEE system is described in a 5-book series:
Data Scientist Improvement Project Roadmap
Step 7 of the 9-step IEE process states ″Identify and execute project.″ This identified project step is to improve a baselined performance metric that is reported at a 30,000-foot-level predictive-metric format (Step 6). Improvement projects can be implemented using several different approaches, where the emphasis is given to improve the metric. One approach is Lean Six Sigma project execution roadmap format; i.e., Define-Measure-Improve-Control (DMAIC).
Data Scientists benefit when using an enhanced DMAIC roadmap approach for project execution as is described in detail in Integrated Enterprise Excellence Volume III. This IEE DMAIC roadmap structure provides a consistent approach for Data Scientist when executing an improvement project:
The IEE Volume III book provides Data Scientists the details of executing this enhanced DMAIC roadmap for organizational improvement efforts including:
- A predictive performance baselining methodology for Data Scientists in the Measure Phase
- A detailed chart for guiding data scientists toward the best tool to select for analyzing process data for the determination of what appropriate hypothesis test to undertake to gain insight to what might be done to improve the baselined process metric
In summary, this IEE book provides a roadmap to structurally evaluate process data relative to make an improvement.
Data Scientist Execution Roadmap Implementation
Contact Us to set up a time to discuss with Forrest Breyfogle how Data Scientists can gain much from an Integrated Enterprise Excellence (IEE) Business Process Management System understanding/implementation.