A fascinating talk at the SAS Global Forum Executive Conference focused on text analytics, one of the newer weapons in the arsenal for analytic understanding.
Dr. Goutam Chakraborty, a marketing professor at the Spears School of Business, Oklahoma State University, described how he’s seen text-based insights expand knowledge beyond the numbers. He spoke of previously unknown facts that made companies more responsive and effective.
His work shows that most analytical models are pretty good at predicting future scenarios and describing conditions. However, competitive pressures and dynamic market conditions leave little room for substantial improvement in existing algorithms. Marginal gains are possible by tweaking existing algorithms, fine tuning parameters, distributions and the like.
But sweeping advancements are likely when we incorporate new types of information into existing analytic paradigms. Text data, for example.
In case studies from different industries, Dr. Chakraborty shared how quantitative returns jumped substantially when text analytics were applied to operational data. For example:
- Automating SMS text message classification and sentiment scores within mobile logistics applications reduced professional drivers’ response times.
- Debt collection increased when call agents were armed with new intelligence from call center conversations.
Besides operational improvements, he also gave strategic planning examples. In one case, merging text-based insights with numeric data improved predictive accuracy of future conditions so intervention strategies were more effective. In another, fact-based understanding of reputation (by tracking the impact of controversial statements in social media) led to better social media strategy.
Text analytics extends existing analytic methods, answering questions such as:
- Why is this happening?
- What should we say?
- Who needs to take action?
If the Q&A after Dr. Chakraborty’s talk was any indication, the audience agreed that text analytics could help them make better executive decisions.
Executives’ words reveal their fitness to lead
Did you know that text analytics can also help decipher what makes a good executive in the first place?
ghSMART is the elite consulting firm that helps CEOs lead at full power. Based on their branded method of assessment (called SmartAssessments), along with their expertise in understanding human behavior, they answer the question: Who should run your business? And now they, too, are seeing how text analytics can be used to advance insights.
In a collaborative project with SAS, some of the early findings of this study are indeed, quite intriguing. Based on analysis of anonymized transcripts of candidate interviews and SmartAssessment ratings, we’ve found:
- Lower-rated candidates used the term ‘mentor’ (and its stem variants, mentoring, mentored, etc.)
Initially, the team believed this to be counter-intuitive. One of the benefits of text analysis is that you can dig deeper into the rationale of a result – and understand what is driving statistically significant numbers. It turned out that the distinction was really that lower-rated candidates described their mentors or expressed wanting to be a mentor, whereas higher-rated candidates talked of being a mentor to others in the interview.
- Candidates with a consulting background were statistically more likely to successfully transition directly into executive-level positions than those without consulting experience.
Here’s a helpful nugget for aspiring executives: Acquire broad experience from working with all aspects of a business (even if in a smaller company) prior to your CEO interview
- Lower-rated candidates frequently described some form of failure, setback, or disappointment throughout the interview.
Telling the truth is important. Context is too. What seems to matter in these preliminary results is how much the candidate focused on describing previous failures in relation to the length of the interview (specifically, the number of words in the full dialogue transcript).
Actionable intelligence from analyzing text is helping organizations reduce risk, lower operational cost and inform both tactical and strategic decisions. And, some exciting new research suggests that text analytics can also help decide who should be at the helm of the organization. Having the mindset of being a mentor as a CEO, for example, calibrates to being more effective leader than simply being successful in the CEO role.
SAS and ghSMART continue to sift interviews to see what sets Grade A executives apart from the rest. We look forward to sharing what we’ve learned later this year.