Data Illiteracy: How Data Professionals Can Drive Change

Introduction

As the world reliance on data continues to grow, the mastery and knowledge of the best way to harness it becomes a vital key to business survival. With an increasing adoption of substantial volumes of data, there is a growing demand for data literacy in employees. However, many organisations face a significant challenge: their workforce is not data literate, that is, they cannot handle data appropriately. This absence is revealed in various aspects such as operational inadequacies, wrong decisions made because of the misleading data, and failure to harness the potential for growth and innovation due to lack of data literacy skills. What we are witnessing is the transition of data literacy from being a technicality of a few IT or data personnel into one of the basics skills that is expected of each employee.

The Growing Significance of Data Literacy

It is predicted that human-like conversations and cooperation with machines will be prevalent by the year 2025: the overwhelming number of employees report using data to make improvements in almost every aspect of their job by the same year. However, for this to be plausible, employers must first seek to close the data literacy skills gap within their workforce. A study conducted by Forrester research on behalf of Tableau estimated that 84% of managers in the U.S. expect their subordinates to have basic levels of data literacy. Unfortunately, a recent survey highlighted that in this regard, only 51% of the employees stated that their organisation offers rudimentary data literacy training. This strongly negates what leaders perceive to be important and what they are currently spending their money on.

Also, a Harvard Business Review Report equally shows that most of the company leaders understand the impact of data literacy, to mean that a whopping 90% of them deemed it crucial for their organisation. However, when it comes to the confidence level of these employees regarding their data literacy skills, the result is quite a shocking one that reveals only 25% of the employees expressed great confidence in their data literacy abilities. And once more, the expectations that leaders have from the workforce are not met by the circumstances inside the company. This disjunction whereby leadership rightfully identifies data literacy as critical, but employees are not equally as convinced of their skills in the matter underscores the imperative of organisations to invest in data literacy training. If organisations do not make right investment on these key competencies properly then these fail to achieve strategic goals and objectives, and they also lose opportunities.

How Data Illiteracy Costs Businesses

Real world examples and multiple research studies that point towards data illiteracy in organisations and its high price is as follows: organisations that have low data literacy levels suffer greatly since a business’ output rates and its accuracy drop dramatically, translating to millions in losses. On the other hand, when organisations decide to invest in data literacy training, they experience motivating enhancements to their tactical positioning and revenue-making environments. This has been broadly supported by the IDC world data forecast indicating that there would be as much as ten folds increase by 2025, thus further highlighting the continued need for data literacy in the workplace. The results that have been derived from the research show that organisations that possess rich data literacy achieve up to 5% higher enterprise value, which is equivalent to $320-$534M.

Financial Costs: Due to the disadvantages discussed in the previous sections about data illiteracy and operational inefficiencies, organisations are most likely to incur additional costs due to additional resources being deployed to correct mistakes and compensate for inadequate skills. In such environments, what happens is that simple data related activities end up taking longer to complete. This, of course, leads to multifold increase of business operational costs. A study by Gartner also revealed that bad data is costing businesses on average approximately $14.9 million every year and that approximately 2 out of 3 organisations aren’t even tracking the cost of having bad data. Moreover, IBM established that poor data quality costs the U. S economy about $3.1 trillion per year. While these numbers are staggering, they are likely to only represent the tip of the iceberg of the total cost of data illiteracy.

Time Costs: As explained above, when employees struggle with data-related tasks, valuable time is often wasted in searching for data and fixing errors. This lack of data literacy is estimated to be costing organisations five days per worker per year; an equivalent of 2% working days lost.

Opportunity Costs: Many of the questions that business leaders have can be answered by interrogating the existing data that resides within their organisations. However, to get that value for the firm they first need to know where to look for it, what to look for and how to interpret it. Again, if an organisation lacks the data literacy that will enable it to mine the data it has then the data becomes useless to the organisation since it cannot be used for decision-making and can also not point out the next line of business that needs to be ventured into. If properly applied, business data can give information on how the customers are receiving their products or services and how they could be approached on possible ideas for the creation of new products.

Poor Decision-Making: If employees don’t know how to use data correctly, they may be left guessing and usually make wrong conclusions. Even though not all these decisions can be described as fatal, they can, on the same note, be somewhat big enough to impact the company’s bottom line. A typical example of this would be misinterpreting the customer sentiments towards a particular product.

How Data Professionals can Influence Change

While the effort of achieving data literacy across an organisation can be challenging, it is, however, true that data professionals should perhaps try to take a more proactive approach to champion for data literacy. Data professional or specialists are usually perceived by most companies as support resources, responsible for designing the data architecture and building the data infrastructure for storage, analysis and visualization of business data. It is this isolation and confinement of data literate employees in the IT or BI teams that robs businesses of a chance to leverage their skills to develop the data literacy of the workforce. The interaction that these data professionals usually have with the rest of the business organisation mostly is an arm’s length; it is not an ongoing knowledge-sharing process – it is episodic where they come with new solutions to problems and then get on to the next one, without imparting more knowledge to the workers.

Based on such considerations, this article calls for more of these data professionals to step up and take a more proactive part in the development of a data literate workforce.

The following are some of the strategies that data professionals can employ to enhance literacy across an organisation:

1. Introduce Data Literacy into Recruitment

The first level of implementation of data literacy in the workplace can be seen in the process of recruiting people that are going to become a part of the organisation. With the help of data professionals, data literacy can become one of the basic requirements that are to be met. Here the data professionals can consult with the HR department to decide on the criteria of the incorporation of data literacy requirements into the job description and recruitment phase. Incorporating these into the job specification and assessment will make sure that only applicants with a certain level of data literacy are recruited.

2. Invest in Training and Development

Thus, one can conclude that the training and development, when implemented continuously, can bring about long-term positive changes in data literacy across an organisation’s employees. While training may be offered by external service providers, data professionals are uniquely positioned to lead in-house initiatives to coach and train other employees on how to source, analyse and interpret data. Whenever in-house data trainers do training, it tends to be customised to the organisational environment, department, role, or individual employee.

3. Provide Ongoing Support and Mentorship

Having support for months and years and interventions from superiors, such as managers and directors, is a process to have a workforce that feels more confident when it comes to data. I find that through daily training in the form of workshops or one to one training, the understanding and the training which data professional with employee would go through would help employees solve issues to do with data and also help in making good choices in data manipulation, data interpretation and data application. There are two broad categories of mentorship; one is where the process is contained and follow structured procedures of the firm while the other is voluntary and very flexible. It meant that formal programs involved someone to assign to the employee a mentor, who is a data professional and who would assist him constantly. Examples of informal learning programs include twice-weekly check-ins with peers, flexible office hours for mutual teaching and learning, and any manner of collaborative events.

4. Promote a Data-Driven Culture

It is important to promote a company culture that prioritises making decisions based on data. Data professionals can set a positive example by showing the advantages of utilising data for decision-making. To champion the culture of data within an organisation, one must ensure that all the employees embrace data in the working environment at all feasible points. Also, within organisations, data literacy can be promoted through appointing data champions in various departments. They can champion data literacy, help when the need arises and contribute to ensuring their colleagues’ adoption of data practices. We build up a community of data literate individuals which enhances the data literacy culture within the organisations.

5. Leverage Data Quality Reports

Consistently utilising data quality reports to pinpoint and resolve data management issues aids in upholding elevated standards and increasing employees’ understanding of the advantages of utilising data for business decision-making. Data professionals can create, produce and utilise these reports to enhance and maintain data precision and dependability, ultimately guaranteeing that business choices are founded on reliable data.

Data quality reports encompass completeness, consistency and accuracy of data parameters that are useful for datasets. These reports may elaborate on luminaries for frequent blunders such as duality, lack of value, and variations. End-users can also receive data quality reports on a daily, weekly, or monthly basis and analyse the information to find patterns to act on.

It is recommended that data professionals must set out data quality goals and objectives and then standardise them regularly. Measures that could be taken to minimise mistakes include regular data validation and data cleansing to ensure that data is always right even as a business evolves. In addition, Data Stewardship to drive understanding of accountability for data quality among employees.

6. Encourage Collaboration

It is crucial that data professionals communicate with the representatives of other departments to improve organisational data literacy. Collaborating on the data projects is a good opportunity to learn from each other and to build the overall understanding of data responsibilities. For instance, when developing a solution aimed at a certain business challenge, a team that includes representatives drawn from the marketing, finance, and operations departments could offer insights from each of these perspectives. Projects are also important since they provide learning opportunities to the various stakeholders involved in a collaborative project. This is when employees from any department can use and share their expertise as they engage in common cause through data initiatives. Another initiative that works very well in encouraging collaboration is the establishment of a data forum, where employees from different business units meet regularly to discuss all matters related to data. These forums can be used to share ideas on how to solve common business problems and discuss future developments in the data space.

Conclusion

As data continues to increase in volume into the future, the importance of data literacy is expected to grow at a similar rate. Data literacy is predicted to be the top skill needed in the workforce by 2030, to operate in the intricate business environment. There is a lot one can do to reduce data illiteracy and contribute to the positive changes taking place at the organisational level, and data professionals are in a unique position to make a difference. With the inclusion of data literacy in their recruitment systems, training, mentorship, data-driven culture, and focusing on data quality reports, data quality training and collaboration, they can support the call for formation of data literate employees. Overcoming data illiteracy thus becomes a strategic asset that should be upheld as it supports long-term stability in today’s highly contested environment. With data literacy now being adopted across organisations, there is an opportunity for businesses to fully capitalise on their data and experience the outlined benefits, as well as overcoming the challenge of competitors developing similar solutions in other industries.