Organizational Development: Balancing Analytics and Intuition

analytics and intuition

For years, businesses have relied on experience, trial and error, and heuristics to make decisions.  But, change is in the air. Data analytics has added a new dimension to the decision-making process, giving business leaders access to new, previously unavailable insights.

Unfortunately, there may be a split in the business world regarding its use.  While some are skeptical about the move toward analytics, others believe it should be the primary tool for business.  In both cases, they tend to miss the bigger picture.

Analytics was never intended to replace intuition, but to supplement it instead.

A Beautiful Combination

The beauty is in the combination. Analytics provides context to the insights that (most) business leaders already possess.

Two recent books help illustrate this point: The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies, by Erik Brynjolfsson and Andrew McAffee, and Average Is Over: Powering America Beyond the Great Stagnation, by Tyler Cowen. Both provide a glimpse of the many ways technology will change the workplace over the course of this century.

Both books use the example of freestyle chess to demonstrate the potential of partnering human intuition with data processing.

For those who are not familiar, freestyle is a type of chess match where humans partner with computers and compete against each other.  Not surprisingly, there are many instances where computers have defeated a chess master. And yet, humans cooperating with computers have easily defeated both humans and computers acting alone.

The reason behind this is what’s interesting. Computers use probabilities to determine an optimal move.  Humans, on the other hand, rely on their experiences and intuition to identify opportunities and implement different strategies.  The computer provides the raw processing power, while the human provides a superior understanding of the game’s mechanics.

The freestyle chess example is a simple illustration, but it demonstrates something more complex for modern organizations seeking new direction: the potential of depolarizing analytics and intuition.

The Analytics Potential

Leveraging analytics, we can aggregate, process, and understand more information than was conceivable even 20 years ago. Analytics Training is a great way to be able to be able to reach your businesses highest potential as it will allow you to have the greatest understanding of how to read your results and invest that knowledge back into the business.

However, it’s important to note that analytics is based on models. In using it as a tool, we need to understand the basic assumptions and limitations of using a model, and use our intuition and experience to fill in the gaps and enhance the analysis process.

Organizational development is a field full of data. In many cases, there is too much information available for one individual to thoroughly digest, analyze, and interpret.  As in freestyle chess, analytics uncovers the trends, but the human in the mix determines which trends are most relevant. That’s how organizations come to understand which trends are worth further investigation.

By utilizing a broader set of tools through that balance, organizations can improve their ability to process information and understand the world within their walls.  It all comes down to balance. Rather than separating the qualitative from quantitative process from one another, organizational development should be informed by both data and intuition in order to drive the desired outcomes.

How Decentralizing Data Informs a Successful Organizational Culture

data decentralization

With the rapid adoption of technology into today’s organizational culture, data collection and analysis is becoming a common component of the way we do business. However, this new reliance on data brings a new host of challenges, including how to combine and share this information across the organization in order to get as much value out of it as possible.

Every department has unique data needs, and while it’s important to analyze the data for individual departments, managers and leadership need to aggregate departmental data to gauge the overall health of the organization.

There can be huge differences in how departments structure and format their data. So, while combining multiple data sources has significant advantages, the disjointed nature of departmental data formats has led some organizations to rely on a less than ideal “top down” or “one size fits all” approach to analysis.  In some cases this approach can work, but it often forces the organization to follow an architecture that reduces the data’s usefulness within each department.

Attempting to simplify the process by generalization may support the manager’s agenda, but the end results are not nearly as specific or as meaningful as they could be.

So, how can organizations ensure data and its analysis serves the greatest number of departments and people as possible, while still benefiting the business as a whole?  Below are several ideas to consider:

Determine which questions need to be answered.

First and foremost, data has to help us answer questions.  It is essential to clearly articulate which questions are more critical to managers and business units, and to ensure that data can be captured to support those.

Establish similar terminologies.

Despite the likelihood that each department has its own unique culture and terminology, organizations should strive to use a similar language across the board.  This will help promote cross-communication and maintain a certain degree of data integrity for managers.  Where this is not possible, organizations should develop a “translation table,” (i.e. a “Rosetta Stone” for the business) which can serve as the key to understanding the different terminologies.

Agree to a common set of core variables.

Each department has its own set of questions that will require a unique set of data, but managers need to address questions that span departments. To ensure they can, organizations should agree on a core set of variables that each department will collect.  This can be something as simple as time, location, identification number, costs, and labor hours, etc.  The key is to agree on how these variables will be defined and documented. Yes – that could require a bit of time and finesse. While this may be the most taxing part of the process, it is the most critical in the data decentralization process.

In an ideal world, individual departments and leadership would easily find a compromise for their various data needs.  On the one hand, each business silo need data that is specifically relevant to their operations. On the other hand, managers need data sets that address broader questions and issues. If the overriding concern is real usefulness in the data, the time it takes to create systems that allow for both will be well worth effort.

How is your organization decentralizing data to inform your culture?