The ability to translate huge data sets into a unified, meaningful view ready for taking action is an essential skill in our increasingly online & data-driven world. Armed with the honesty of clean data, Learning & Talent teams work together to maximize the performance of your company’s most valuable asset –your workforce.


Trustworthy data helps businesses zero in on the strengths and weaknesses of employees, supervisors, and managers, weed out inefficient training courses, detect and mitigate poor employee engagement causes, and assess current skill levels and gaps. Data also demystifies the art of attracting and retaining top talent, uncovering why employees stay, why they go, and what decisions will impact either choice and to what degree.

Or at least it’s supposed to…

In truth, Learning and Talent Development teams are drowning in data instead of harnessing its power. But attention isn’t given to the “what” and “why” behind data collection which leads to heaps of purposeless data and literal gigabytes of clutter.


3 Big Data Challenges That Hinder Learning and Talent Outcomes

1. Too many data gaps:
“Who are my top performers? What areas need attention immediately? What are we currently spending too much time on and what are we ignoring?”


The answers to these questions are critical bits of knowledge to have, but very few businesses have great answers for them. That’s because their data either isn’t collected at all, the data they need is very difficult to locate, or the data collected is just flat-out inaccurate and doesn’t tell a complete story. Without this critical information, your management team will not have the tools they need in order to make meaningful decisions for your business.

2. The ‘What Reports’ problem: L&T divisions, across many organizations, have no idea what reports to create to best showcase specific data. Report generation is an essential part of the job, but too many reports can create information overload and prevent employees from making the right decisions.  Also, reports & dashboard needs will vary based on the stakeholder who requires them, and so understanding the reporting profiles of all key stakeholders will ensure that good data doesn’t end up in the wrong place.

L&T staff have too many metrics crying for their attention; it can be an overwhelming endeavor to figure out where to start.  Without clear priorities and a focus on what needs to change and how we expect that change to occur, many end up accidentally sifting out critical data and keeping in redundant facts and figures, which results in ‘Garbage in, Garbage out’ — i.e., the gathered analysis from irrelevant data isn’t useful nor sound.

3. Inefficient reporting tools: Many organizations utilize LMS and TMS reporting tools that are either too complex or too basic to generate the right level of reporting. Staff members ended up having to export and then process vast amounts of data manually to create and distribute even the most basic of reports.

This can cause expensive delays in getting the right information into the hands of the right people at the right time. Businesses should strive to adopt lean automated processes that allow for the generation of quick, accurate, easy-to-understand reports that are well-organized, and easy to disseminate.


Interested? Click here to sign up for a FREE ½ day workshop with Bluewater learning experts today! Enter FREE 1/2 day workshop into the Message field.


Get the Right Data Heard by The Right People

Data in the wrong hands tells no story. To the irrelevant eyes, they are just random sets of numbers worth noting. But, present it to a supervisor, and their face will be lit with enthusiasm seeing a progress report with key performance index data for the month.


L&T development should make it a priority to adopt procedures that swiftly sends all reports to appropriate members promptly. They need to be diligent about which data elements matter and are accessible by whom.  Too, setting expectations for actions to be taken once data is received and reviewed is critical – “what should we do based on what we see?”


Data Increases Reliability by Eliminating GuessWork

The bedrock of L&T is factual data. Hunch-based decisions (for example you think a manager needs specific training) without data support isn’t a reliable way to make decisions in support of your people.


An erroneous, instinct-based decision can trigger thousands of dollars worth of losses for a business. It can cause businesses to make faulty decisions like giving a certain employee a bonus to get them to stay longer with the company when data shows an increased paycheck isn’t what they want to be happy, but access to more ongoing education is actually the key.

Data eliminates the need to solely “follow the gut” by giving you concrete proof in the form of feedback, performance score, and other metrics to determine what kind of training an employee might need, what they know and what they don’t know, etc. Processes like Data-Driven Decision Making (DDDM) should be adopted to make organizational decisions based on data rather than intuition or observation alone. It minimizes the risk of bias affecting the quality of decisions and gives your company access to real change-making information.  Where data and instinct intersect is where the true magic happens.

Subsequently, skills-based development and learning in the flow of work can be then implemented to increase satisfaction and engagement, and develop people’s capabilities by making learning central to their growth.

To identify things like skills gaps, develop the right learning journey, and then measure their impact and efficacy, excellent and clean data is essential, without any present data gaps leading us down an incorrect path.  Key decision-makers are then enabled to identify critical pockets of growth opportunities and then evolve the plan of action based on actual performance results.


Nurturing Growth

Your employees are your future, and the Learning and Talent departments are central to nurturing and accelerating the growth of their skill set through relevant training. L&T can multiply the number of top performers in your team and create a culture that attracts and retains the best.


The future of Learning and Talent organizations lies in data!

The primary focus for your business should be to gather only the data that matters and get it to the right people so that it can be transformed into ground-breaking action that uplifts your employees as well as your business outcomes.  Creating true accountability models based on anticipated outcomes and tracking progress towards those outcomes will allow you to make more effective and accurate adjustments on the fly, allowing your business to keep up with the speed of change.


Most Importantly, how to Get Started!

In order to start making meaningful decisions with your data, you will need to develop an effective Decision Analytics Framework. This will allow you to do the following:


  • Identify and/or prioritize key decisions that your organization needs to make.
  • Identify the key questions that need to be answered in support of that decision
  • Define specific data points that are needed to answer the key questions
  • Determine stakeholder needs for reporting as well as how to plan for effective data aggregation, tracking, & refinement.

These simple steps will allow you to perform meaningful actions like prioritizing your decisions' organizational impact and measuring the change to your business. It will determine the right starting point for you as well as show you the cost of doing nothing. Finally, it will force you to ask better questions in order to create cultural changes as well as analyze the resources you currently have and what you might need for the future.

If this seems like a lot, do not worry!

Bluewater has created a ½ day whiteboarding session to help you create an amazing Analytics Decision Framework that will create an immediate impact in your company.

Interested? Click here to sign up for a FREE ½ day workshop with Bluewater learning experts today! Enter FREE 1/2 day workshop into the Message field.