Culture, Communication, and Engagement

If it isn’t broken…

Don’t fix it… but how do you know if your culture is broken? What do you do even if you know it is?   Where Workforce Analytics meets traditional Organizational Dynamics often can be the roadmap to improving your culture, diversity and in turn productivity and profitability.

Historically the pulse of an organization was difficult to measure to a useful degree. That has changed due to advances in technology, proliferation of data, and HR job specialization and internal re-evaluation of employee career objectives.

If your organization has been delaying a big data initiative for HR this is a good first step in discovering what it can reveal.

Engagement & Culture Analytics Dashboard

Surveying data across organizational and people dimensions allow breaking down of the population more easily.  This leads to real actionable insights when coupled with Workforce metrics by the same dimensions.

 

Satisfaction vs. Engagement vs. Sentiment

While these are all undoubtedly correlated measures, it’s important to understand the nuances of these words in the context of surveys:

  • Satisfaction is a term lifted from “customer satisfaction” but is most often synonymous with Engagement when applied to employees. However, it’s important to recognize that the words do matter so it is important to maintain a a consistent label between the two.
  • Sentiment refers to the degree of negative and positive emotions connected to an answer. Sentiment is NOT the same as Engagement and you can have employees who actually perform better when engaged but are not “positive”.  One can be engaged as a pessimist and can be disengaged as an optimist but these do tend to correlate on average.
  • Engagement is the relatively newly coined term most companies seem to want to tie back to voluntary turnover metrics.

 

Culture

Culture is a critical component of any successful organization and transforming it takes a huge amount of change management time and effort.  More challenging is quantifying what “culture” means to an organization and measuring shifts in those measures across social, geographic, economic, technical, legal, structural, strategic and operational lines.

Certain organizational norms (as with people) can make them unproductive and difficult to interact with.   This leads to high turnover and significant losses in productivity due to increased absences, little knowledge transfer, and lack of motivation.  There are new and better ways to effectively measure these shifts that did not exist before.

Culture can be either a growing cancer or the lifeblood of a company.  Early detection is critical in this case as well, the incline in organizational health takes years of effort, but it can take a steep dive in only months.  Areas of your organization which have negative sentiment and low morale will spread to closely connected segments easily by geography, job function, and reporting lines.

 

Culture health has direct correlations to turnover, productivity and profitability.

 

Measuring culture is as much art as it is science, but the most important part of measuring is creating a standard yardstick.  Without this baseline it’s difficult to know where you stand as an organization.

 

Text Analysis and language heavily influence cultural profiles and therefore the questions and content are  usually difficult to translate into multiple languages.  The best approach is to keep phrasing as simple as possible and do not underestimate the need for professional translation which can be highly subjective.

 

We leverage a model which was developed from a cultural model designed for measuring broad cross-country cultural business differences and was adapted to include more person-centric components as well (similar to the one covered here): http://blogs.hbr.org/2014/04/a-tool-that-maps-out-cultural-differences/.

 

This was also built with concepts covered by John Kotter in his book Organizational Dynamics Diagnosis and Interventions  https://www.amazon.com/Organizational-Dynamics-Diagnosis-Intervention-Development/dp/0201038900

Based on the questions answered in our survey and more free word-association included we convert the results into two parts:

  • A scale based on a continuum of typically opposing (but not mutually exclusive) dimensions of culture (e.g. ‘entrepreneurial’ vs ‘bureaucratic’).
  • A word associated text analysis that correlates engagement to particular organizational traits described on the scale

They are represented as a Word bubble below,  Engaged vs Disengaged Word usage, and  the derived Culture Continuum scale:

Culture Word Frequency

Survey Anatomy

 

If there are 50 questions on a survey, compiling data and finding all these relationships and then tracking changes to responses over time takes a tremendous amount of manual time and effort.  Many companies may disregard the work as unnecessary expense or not high visibility enough to warrant funding on a long term basis.  However, there is much to be gained in organization dynamics  and productivity improvement for most organizations.  Delving into the details can reveal some interesting characteristics introduced below.

 

 

Standard Deviation

A well rounded survey question may have a mean response of 50% of the total scale (for example, 2.5 on a scale of 1 to 5).  Each question will also have “volatility” characteristics indicating how widely answers vary on the scale.  In addition, each question will often have negative or positive emotional correlations as well as correlations to other questions or keywords.

 

A low volatility (standard deviation) for certain questions indicates similarity in all answers.    Take the following example:

  • the (1 to 5 scaled) agree/disagree statement being evaluated is “Colleagues come and go often, very few co-workers have been in my group or company over 5 years.”
  • the sample survey resulted in an average/mean of the answers of 2.9, very close to the 2.5 midpoint and the standard deviation was 1.38. This indicates answers varied widely (almost across the whole scale of 1-5 and  were very volatile).

 

Assume in year 2 we ask the same question and now the average answer is 2.5 and the standard deviation goes from 1.38 to  1