Unmasking Corporate Culture: AI-Powered Insights into Honesty & Integrity
“They will tell you to lie to clients in order to make their numbers.”
“False claims of no accidents in 19 years.”
“They act like they want to improve conditions and work culture but that is a complete lie.”
These anonymous employee opinions, stated in public for all to see, were each made about three different publicly traded US-based companies. What sentiment do they convey? Are they credibly indicative of employee experience? Do they tell us anything about corporate culture? Or possibly even business performance?
With the benefit of AI combined with data at scale, we can address these questions with the Aniline Employee Perception scoring model.
That’s because these opinions are not isolated: they exist as data in a massive NLP (natural language processing) model built over the last 4 years, encompassing hundreds of millions of employee perceptions about where they work.
We characterize these particular opinions as negative expressions about the experience of honesty within an organization. By combining all related positive and negative sentiment, this enables us to model how employees perceive an organization's truthfulness and authenticity.
In turn, our measurement of honesty combines with measurements of other selected attributes — specifically how employees experience their employer’s mission, values, commitment, ethics, and compliance — to form a broader measurement of organizational integrity. This categorization scheme, or ontology, is shown in the figure below depicting Aniline’s complete scoring model:
Aniline Employee Perception Scoring Ontology
Prompted by a recent news story about US agribusiness company Archer Daniels Midland (ADM), we investigated their integrity score on our user platform. Here is a portion of ADM’s employee perception dashboard as of our most recent monthly update on December 31, 2023:
Zooming into the integrity score brings up its components from the ontology:
While these scores indicate a mix of positive and negative sentiment, ADM’s Honesty score of 12 stands out as particularly low, so low that it ranks among the lowest 100 Honesty Scores we calculated for US public companies on that date. Importantly, we are not characterizing whether or not this particular score had anything to do with ADM’s recent event. What we are saying is that the voice of the employee is available and can be assessed quickly and effectively through the use of AI.
Whether in isolation or in combination with other employee sentiment metrics, could employee perception data represent an indicator for organizational performance? To date, we have validated the predictive power of Aniline scores for workplace injuries. In short, culture drives risk. We invite you to determine whether culture, as measured by employee perception, also drives business performance.
Aniline’s unique approach to understanding the collective voice of employees in real time helps to elevate performance by revealing what drives success. To learn more, please visit our website at www.aniline.ai or contact us at info@aniline.ai to schedule a brief introduction to our generative AI solution.
