Building organisational resilience with learning analytics

Enterprise training sits at the intersection of 2022’s leading business concerns: adapting to supply chain issues, workforce distribution, employee turnover and increased onboarding. 

 

Because of this mission-critical position in the organisation, data generated and captured by training teams has the potential not just to demonstrate the response to business challenges but to anticipate them. Bringing a business intelligence perspective to training is how leading programmes are building resilience for their organisations.

 

Forming that intelligence through a learning analytics architecture is the first step. Harnessing training data to infer opportunities, identify risks to productivity or compliance, and forecast the impact of environmental variables transforms response into resilience. Ready to empower data-driven decisions in your organisation? Here’s how to get started.

 

How to design a learning analytics blueprint 

 

Begin where you are. Consider this overview of four types of data analytics, how your programme may be leveraging them already and what it could look like to evolve toward greater training business intelligence.

 

Descriptive analytics: what happened

 

Every training team gathers activity reports, but what may be missing is the relationship between events. Tracing this relationship is how analytics drive opportunity.

 

Reports you’re probably running:

 

 

• Demographics. The overall number of learners and populations.
• Course fill rate. Which courses tend toward empty seats, despite their importance?
• Course completion. The rate at which learners fully finish the course – or not.
• Compliance. Have learners completed the required training and applied it?

 

 

 

Activity reporting will always be important, but placing activity into context is where the business intelligence value awaits. Can you affiliate training activities to populations or cohorts within your organisation to identify gaps or opportunities in the areas of the business they serve? What about costs: what are the correlations between course activity and per-learner costs that impact your training ROI? Your learning analytics design can install this crucial context.

 

Diagnostic analytics: why it happened

 

Root cause analysis of learning outcomes is crucial to substantiating the need for training as well as revealing its business impact. 

 

Reports you’re probably running:

 

 

• Certification. Certificates, achievements and their expirations.
• Version control. Course content date of revision and required update.
• Timeliness. Occurrence of training vs individual performance outcomes.

 

 

 

Interrogating business trends that reveal themselves early via the training function is where training leaders begin leading the business. Do your training reports map individual contributor training activities to business KPI outcomes? Where did training of key populations not only meet the demands of the business but demonstrate contribution to success? Diagnostic analytics are engineered to reveal this.

 

Predictive analytics: modelling trends to future scenarios

 

Enterprise training teams operate an average of nine to 11 different software tools. Each system represents another disconnected data source. That makes predictive analysis difficult but even more important.

 

Reports you’re probably running:

 

 

• Onboarding forecast. High turnover and hiring challenges are driving the real-time impact of this report.
• In-person to video-based training gaps. The pandemic established tracking for many industries that rely on person-to-person knowledge transfer. Anticipating where certification gaps may occur if in-person training is not available is vital.

 

 

 

Modelling data for future needs requires the ability to connect all your data to iterate against scenarios with multiple, dynamic variables. How can you harness AI tools to connect your data sources and craft relevant, dynamic models for your organisation? These tools exist, and it is one way leading teams are steering through uncertain times.

 

Prescriptive analytics: forecasting success via patterned predictions

 

Training teams often rely upon the wisdom and experience of staff rather than data when it comes to forecasting success. While perspective is essential, a prescriptive data framework can empower your team to make business intelligent decisions faster and with more autonomy. 

 

Reports you’re probably running:

 

 

• Compliance achievement. Anticipated impact of future regulatory changes and the investment required to meet these standards.
• Content development forecast. Plan for what content will need to be created or renewed based upon the strategic plan for the business and evolving environmental needs. 

 

 

 

Modelling realistic scenarios and their variables becomes most useful when you can apply those points of view to forecasted data. What training will be needed when matriculating new hires from onboarding to optimal performance, and how long will it take to render a positive business impact?

 

How to architect business intelligence for training
In 2022, training will lead business or cause it to limp. Harness the power of your training data now to evolve a business intelligence approach for your training department. 

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Get started at getadministrate.com/blueprint

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By John Peebles, CEO of Administrate