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Developing Data Literacy with Training Simulations

Jeremy Lovelace

Jeremy Lovelace

Data literacy was once seen as a niche skill possessed only by specialists. However, it is now a cornerstone for all sales executives. Indeed, the ability to “speak data” is essential if they wish to extract value from customer relationship management (CRM) and sales performance management (SPM) software — something that many experienced sales directors have identified as being a struggle for most if not all organizations.

In order to address data literacy gaps amongst reps and managers, sales trainers are increasingly turning to computer-based business simulation games. Already an established learning tool, these simulations can develop data literacy in sales teams thanks to two key attributes; the datasets upon which they are based, and their ability to reinforce the practical benefits of data-driven decision-making (DDDM).

Realistic commercial datasets

One challenge facing trainers tasked with developing data literacy in sales forces is to find a way to make basic data analytics both interesting and relevant. This is where training simulations excel.

Based on complex, realistic (or even actual) commercial datasets, such simulations may include every type of data typically available to a sales organization, including demand, market share, competitor pricing, customer sales, and internal resource data for example. Thus, simulations are able to provide an immersive ‘data experience’ to learners, and by giving them an opportunity to interact with data in a fun, gamified training context, they accelerate the development of data literacy.

However, effective decision-making is based not just on a basic understanding of static, descriptive data, but also on an ability to understand dynamic changes in data and adjust decisions accordingly. This leads to the second key attribute of computer-based training simulations that drives their ability to develop data literacy — they instill the importance of so-called ‘data-driven decision-making’ (DDDM).

Data-driven decision making

DDDM is defined as using facts, metrics, and data to guide strategic business decisions that align with your goals, objectives, and initiatives. Although this sounds great in theory, the reality is that even when given powerful analytical tools (e.g., CRM and SPM softwares that facilitate DDDM and the optimization of sales activities), sales reps and managers are often still more likely to make decisions based on inertia and existing relationships.

This is where training simulations can be a game changer: by taking learners through a series of decision cycles in which they see the positive consequences of DDDM (and conversely, the negative consequences of ‘winging-it’) in a realistic commercial environment, simulations bring the importance (and ROI!) of data literacy to life.With this attribute, many companies even use simulation-based training workshops as a lead in to their annual sales strategy planning and budget setting initiatives.

A data-driven future

Ultimately, data literacy gaps are something with which most, if not all, sales organizations will have to grapple at one point or another.Investing in closing these gaps and developing data literacy among sales forces is not only part of keeping up with times, but also a potential driver of a competitive edge in an increasingly volatile and dynamic commercial environment.Given this, simulations — with their ability to drive the development of data literacy -—should become an increasingly relevant methodology for pharmaceutical sales forces.

Jeremy Lovelace is the founder and director of HFX Training






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