Data Use in Decision Making - Summary of Doctorate Research

How do business leaders use data?

By Chris DowsettT: @ChrisDowsettW: http://www.DesigningData.co

v1 May 2015

Summary of results from my Doctorate research on

Data use in decision making

My research primarily focused on two questions related to how business leaders use data:

1. What factors influenced the selection of data sources by senior business leaders in decision making?

2. How did those factors impact the way data sources were used by senior business leaders?

The research focus

This research was part of a four-year Doctorate program with the University of Southern Queensland.

This was an exploratory research project that included a mixed-method approach.

Data was collected across four phases:

• Literature review

• In-depth interviews via telephone

• Survey of business leaders

• Case study

Research background

My research deliberately targeted senior business leaders at the Group Manager/Director level through to C-level executives.

The research included:

• 111 Senior business leaders surveyed

• 13 In-depth interviews

• 1 Case study

Research respondents

At the top level, the results fell into three findings. Each is explained in more detail on the following slides.

FINDING 1: Data hierarchyBusiness leaders used a variety of data sources based on a subjective hierarchy unique to them. This subjective hierarchy determined what data sources were used and valued by a business leader in decision making.

FINDING 2: Subjective influences involvedBusiness leaders selected and used data sources according to a set of four influences. Those were: personal experience, time, organizational bias and project factors.

FINDING 3: Lack of data maturity and integrationData use maturity varied amongst organizations. Many organizations lacked an integrated approach to data use.

What I found in my research

Finding 1: There is a data hierarchy

What I found

• Most business leaders used some form of data in their decisions however data use varied. Some used it objectively while some used it to support existing decisions.

• All data wasn’t equal. The same data source, such as database analytics, was used differently by different business leaders.

• Data sources were used and valued according to a hierarchy that varied by each individual business leader. This hierarchy was determined by the factors in Finding 2.

• Generally, internal customer database metrics and analytics were considered the most valuable data source followed by industry trends data and then customer survey data.

Business leaders used a variety of data sources based on a subjective hierarchy that was unique to them. This subjective hierarchy determined what data sources a business leader used and its importance.

Finding 2: Four subjective influences involved

• The research showed a data source was not necessarily selected based on merit. Instead, business leaders selected data based on a set of four subjective influences.

• The four subjective influences that determined whether a data source was used were:

1. Personal experience - a business leader was more likely to use a data source if they’ve used it before.

2. Organizational demographics - organizational factors were shown to influence what data sources were used. For example, industry, whether the business was innovative or entrenched, business strategy and culture.

3. Time-based requirements - data sources available in a shorter amount of time often won even when less accurate.

4. Project requirements - more sophisticated organizations ensured measurement was planned into projects. However less sophisticated businesses had an ad-hoc approach to data use.

What I found

Business leaders selected and used data sources according to a set of four influences. Those were: personal experience, time, organizational bias and project factors.

Finding 3: Lack of data maturity and integration

• There was a mix of maturity and sophistication to data use. Some businesses had a clear, well documented structure for managers to follow while others didn’t have any processes.

• Many businesses lacked a central resource or location for sharing data insights and analysis. This often lead to the duplication of work and disconnected teams.

• Data sources were used inconsistently - often within companies. For example, teams within one company used different data sources to evaluate the same project. This led to conflicting results and reduced confidence in data.

• Data silos and poor communication of data insights between managers created multiple inefficiencies.

What I found

Data use maturity varied amongst organizations. Many organizations lacked an integrated approach to data use.

What next?

• Realize there are subjective influences involved in how data is being used - meaning business leaders are not always using the most accurate data.

• Invest in structures, tools and processes that support managers in using the best data sources for the project. For example, ensure measurement frameworks are used and there is enough project time allocated for examining data.

• Focus on the user experience of data – that means ensuring dashboards are user-friendly, analytics are easy to interpret and communication is clear.

• Check out the ICSAR Model for data use that I created from this research. The ICSAR Model is a five step framework for improving data use and designed to avoid the subjective influences highlight here. Go to http://www.designingdata.co to view and download the ICSAR user guide.

How to use these results now

This research has shown businesses need to examine how data is being used within organizations. It highlights the need to invest in tools and structures that help managers use the most accurate and objective data.

Thanks for reading.

If you’d like to learn more about using the ICSAR Model framework – please visit: http://www.designingdata.co

By Chris DowsettTwitter: @ChrisDowsett