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Data fluency is a critical business capability, but in my experience working with many different organizations across a variety of sectors, it’s easier to tell the companies that aren’t data fluent from the ones that are.
This post is written by QuantHub contributor, Jennifer R. Burnett, Ph.D, President of Caliber Talent Solutions.
The necessity for organizations to embrace and leverage data for all types of business decisions has led leaders to continue to invest in their data capabilities such as machine learning and artificial intelligence. But being fluent in data is an organizational capability that extends beyond the data experts.
Why Employees Should Be Data Fluent
In fact, I would argue that every employee must have the ability, and, more importantly, the confidence to understand, interpret and use data at a level of proficiency relevant to their role. In the most data-fluent organizations I’ve worked with each person plays a role to guide, translate and apply data-driven insights for the business.
By ignoring or underestimating the need for data fluency throughout the organization, a company takes the risk that:
(1) data results are misinterpreted or fail to translate into meaningful business applications,
(2) end users do not value or know how to use the data results,
(3) leaders do not reinforce and encourage a data-driven culture in the organization.
1. Data experts need data translators
I have worked with data experts who are very well versed in the business, but they still rely on business experts to help translate results into meaningful insights. A data translator is able to clearly, and seamlessly connect the data results to the impact for the business. Without a data translator to provide context, give credibility, and communicate the meaning and importance of the outcomes, the data may be misunderstood, misinterpreted, or never be used as intended.
However, in this case, the HR team was unprepared, lacked the data fluency to fulfill that role, and felt uncertain about using the data. The CHRO realized they needed to educate every person on the HR team and develop their confidence in their ability to own the data results, interpret them using their knowledge of the business context, and skillfully communicate the insights to influence talent decisions.
While the data analytics team may be doing the heavy lifting on the analytics side, with a data translator, the results go from being ‘just numbers’ to having real meaning and impact. I have seen that business experts get excited about receiving support from advanced analytics team members, but that often isolates data literacy deficiencies amongst their team members. For this reason, it’s critical to build the confidence and proficiency of team members who are translating and communicating results.
2. Data analytics only matter if the results are used
Every solution arises from the need to solve a problem, gain efficiency or reduce risk/errors that will benefit an end user of the data-driven solution. The data end users are those individuals who will receive the data-based outcome and determine whether it has value and should be used to make decisions, perform work, change behaviors, and adjust strategies. If data end users do not understand and/or value the results, insights, product, or recommendations, then there is not much incentive for them to use that solution.
Sales teams are a great example of where I’ve seen this happen. Sales organizations produce a ton of data about the sales process and the many variables impacting deals. Sales data is often readily available to sales representatives and leaders, but it can be quite complex, including predictions of pipeline strength, win rates, loss reasons, and forecasts. I’ve seen sales teams struggle with a more data-driven approach because it is easier to stick with what has worked in the past. They focus heavily on the “art” of sales rather than having a good balance with the “science” of selling. The data might exist, but until the data is embraced as a valuable tool to guide actions and decisions, the benefits will not be realized.
The data end users in any organization will ultimately be the ones who determine the value of the insights being produced by the data experts. The greater their own data fluency, the more likely they are to experience the positive impact of incorporating data insights and continue to develop these skills.
3. Data fluency starts at the top
Organizational leaders are not typically data experts themselves, but they play an important role for the organization to embrace an analytics mindset and create a data-driven culture. To fulfill the data-driven leader role, they must be fluent in understanding the context of the data and purpose of the analysis in order to guide the analytics experts to provide meaningful business insights.
Unfortunately, it’s easy to spot leaders who lack data fluency themselves. Leaders who are less data fluent, may express more concerns and be less likely to embrace all the benefits that come from more data-driven decisions. I experienced a situation where one executive in a manufacturing organization, was shown the results of an analysis that indicated a lack of adequate skill development for critical roles, creating a compliance risk and loss of productivity. This data had not been presented in this particular way before and the executive’s first reaction was to say, ‘the data must be wrong.’ The data was accurate, but it was uncomfortable for that leader to hear the news.
I think it’s critical for leaders to lead the charge of becoming data fluent and setting an example for all employees as they pursue their own growth in developing stronger data skills. The importance of data fluency for leaders is for them to understand the context of the data, the purpose of the analysis, and to have confidence in applying those insights to improve the business. In turn they are more likely to encourage exploration and uncover opportunities for data-based solutions to move the business forward.
4. Data fluency creates a powerful organizational capability
In spoken or written language, educators refer to fluency as the bridge between words and comprehension. It is the same for data capabilities – fluency is the necessary link to move from data and numbers to true understanding, valuable insights and impactful application.
When data fluency is seen as an essential organizational capability; the company can truly realize the power of having a data-driven culture. Each person who creates, analyzes, translates, interprets, and uses data is in a position to provide input and feedback that continuously improves the data and analytics process. I believe as companies recognize the value of data fluency at all levels of the organization, they will excel in their field and realize a competitive advantage. It starts with leaders acknowledging a lack of data fluency, and actively investing in closing that gap. Then they can begin building a better, stronger data-driven organization.