Data Analysis, the Wrong Start, the Wrong End

Most data initiatives fail to deliver real value to the enterprise. The reason is not the lack of data analysis skills, but the failure to employ analytical skills to address the business side of the initiative. Most of the data analysis projects go through a data-focused process as follows:

Understand what information is needed
Collect data
Analyze data
Present results

Such a process does not provide much value to stakeholders and business.

The Wrong Start

Starting with data, without first doing a lot of thinking, without having any structure, is a short road to simple questions and unsurprising results. We don’t want unsurprising results —we want knowledge.

As professionals working with data, our domain of expertise has to be the full problem, not merely the columns to combine, transformations to apply, and models to fit. Picking the right techniques has to be secondary to asking the right questions. We have to be proficient in both to make a difference.

To walk the path of producing things of lasting value, we have to understand elements as diverse as the needs of the people we’re working with, the shape that the work will take, the structure of the arguments we make, and the process of what happens after we “finish.” To make that possible, we need to give ourselves space to think. When we have space to think, we can attend to the problem of “why” and “so what” before we get tripped up in “how”. Otherwise, we are likely to spend our time doing the wrong things.

The Wrong End

In addition to the wrong start, many data initiatives fail to bring stakeholders to the right end. Analyzing data and presenting results in graphs and charts never leads to unique outcomes. Data consists of observations about the world—records in a database, notes in a logbook, images on a hard drive. There is nothing magical about them. These observations may prove useful or useless, accurate or inaccurate, helpful or unhelpful. At the outset, they are only observations. Observations alone are not enough to act on.

When we connect observations to how the world works, we have the opportunity to make knowledge.

Arguments are what make knowledge out of observations.

The Right Thing to Do

Successful data analysis initiatives should address the business side as well as the data side. To differentiate yourself as a data analyst, you need to acquire business analysis skills. Where business analysts working on data initiatives need to tailor their business analysis efforts to be able to drive insight from data to deliver real value.

This can be surprisingly challenging. The secret is to have a structure that you can think through, rather than working in a vacuum. Structure keeps us from doing the first things to cross our minds. Structure gives us room to think through all the aspects of a problem.

Business Data Analytics is a specialized area of study that contains aspects of business analysis and data analytics disciplines and is used for achieving better business outcomes through evidence-driven business decisions. The business analysis and analytics concepts are useful to both business analysis and analytics professionals alike to generate value for the enterprise through analytics initiatives.