This is the first, in a series of four articles, on Systematic Thinking and the tools and techniques for exploiting data for better insights to render better data driven decisions. In this article we will explore the concept of Systematic Thinking.
The information in the article and more will be covered at JPK Group’s 2019 Analytics Academy. Click here for more information.
Analysts do well when given a specific assignment to analyze from their manager; e.g. tell me which stores have negative YoY sales YTD. They’ll jump into spreadsheets and be back to management shortly. However, ask, which stores have trends that need to be watched, and answers will vary widely or no answer at all. So, why the trouble with the later analysis and not the former?
Because typically the Analyst does not have a methodology to approach data analysis.
Whether in Finance, Operations, Strategy, Marketing, HR, IT, etc. analysts have had little training or mentoring in data analysis and collection. College courses in math, economics, or statistics also do not provide an overarching methodology.
However, engineers are taught, via education and vocation, the skills of systematic thinking. They follow a flow to fix problems and improve performance. This systematic approach can and should be applied to both data analysis and the determination of the data to be analyzed.
For example, if a power plant has an issue, the engineer will whittle-down the problem to the system then equipment then the broken part. The same can be applied to data analysis.
If we go back to the question of trends asked above, an engineer would start the analysis with negative trends that could get worse. Next, he would identify types of trends (e.g. sales, inventory, traffic count, etc.) then select and measure the trend.
In addition to bad trends that could get worse, he would also want to categorize bad trends that could get better so not to waste time to fix that which is already correcting; good trends that could get better so to take advantage of, and; good trends that could go bad to “close the barn door” before the horse leaves.
While this is a highly simplified example, the point is to systemize the thinking, what we phrase as Systematic Thinking. This same process also applies to assembling the data for analysis.
A more in-depth response to the question we started with, is presented on the chain of thinking below that assembles both the question and data. It follows that answers are easy when the question is known, the hard part is framing the “right” question.
Q: What trend is important?
A: Is the store concerned primarily on revenue or cost?
A: If revenue, then what are the drivers of revenue?
> Hypothesis: Foot traffic in the store drives revenue
> Then what could be the driver(s) of foot traffic?
Promotions, store front, merchandize location,
Unemployment, consumer sentiment, product price,
Remodel, road condition, store location, store ingress/egress
Once the question, hypothesis, and data are determined, then comes the application of analytics – but which? This will depend on several items that we will explore in the next article on the Applications of Advanced Analytics.
To Learn More About This Topic
The Analytics Academy offers a class on Systematic Thinking. The Academy is held twice a year about March and September that is designed for directors, managers, and analysts who need to better exploit data.
Join us at the Analytics Academy in San Diego from September 18-19th 2019. Click here for more information and to register!
This article is a collaboration between Robert J Zwerling and Jesper H Sorensen from the organization Finance Analytics Institute (www.fainstitute.com) and is an excerpt from their book, Implementing an Analytics Culture for Data Driven Decisions – A Manifesto for Next Generation Finance. Robert and Jesper are the content creators behind the Analytics Academy and will teaching at the Academy in September!
Copyright 2019 Finance Analytics Institute, Robert J Zwerling & Jesper H Sorensen. All rights reserved. No part of this document may be reproduced without this copyright notice.