Senior Consultant, Data Science & People Analytics Owl's Ledge
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The last mile: turning insights into actions in workplace learning analytics

3rd May 2019
Overcoming the last mile problem in learning analytics
artekSzewczyk/iStock
Overcoming the last mile problem in learning analytics

In part three of a six-part series on workplace learning analytics, Trish Uhl explains how to overcome a common issue – known as ‘the last mile problem’ - transforming insights into positive action that will help steer the business in the right direction

DDI research estimates that 79% of analytics programmes fail due to ‘the last mile problem’ – an inability to turn analytics-enabled insights into actions.

This inability to translate analytical output into operational execution has less to do with deficits in data, data science or statistics, and more to do with a lack of people engagement.

L&D practitioners can avoid these failures in their learning analytics practice by doing the following:

  • Producing outcomes-focused L&D products attuned to stakeholder needs and aligned to business priorities

  • Putting people and work-related insights into the hands of key decision-makers across the enterprise

  • Building and deploying data-enabled L&D solutions directly to the frontline to reduce friction, make work easier and enhance employee experience.

Below I explore in more detail how to begin transforming insights from learning analytics into actions that will drive business success.

Centered vs centric

Start by putting the organisation and its people at the centre of your learning analytics practice.

This isn’t the same as being business and people-centric; it’s deeper than that.

Learning legend Bob Pike taught me the critical difference years ago. Business- and people-centric means about the business and its people; whereas business and people-centred means putting the business and its people at the centre of what you do.

At its core, the primary purpose of building workplace learning analytics capability is to create an insights-driven L&D function that better supports business and operational stakeholders in:

  • Addressing people and/or organisational needs

  • Taking advantage of opportunities

  • Solving worthwhile people and business performance problems

These objectives are what is meant by promoting positive people impact and delivering business value.

The better L&D gets at putting data-enabled people and work-related insights into the hands of key decision-makers to help them make smarter decisions and take more intelligent actions, the more we increase our relevance, value, strategic influence, reach and impact.

Attunement

“Using analytics to prove what you’ve already done was valuable isn’t the right frame. You want to put analytics in the right part of the story – outcome-focused and in service to responding to business questions. Because analytics is only valuable when it's in front of the line of business; when it's in front of somebody who's materially changing a decision.” – Ian Cook, Vice President, People Solutions at Visier Inc.

Executives, line managers and other operational stakeholders do not care how we use workplace learning analytics to improve our internal L&D processes or product outputs. They only care about how those things serve operational needs – and outcomes.

Ultimately the long-term vision of any analytics programme – including learning analytics – is to use analytical capability across operations and functional areas as a driver for broader business strategy.

Quick wins allow L&D to deliver value and build stakeholder trust and equity early in an analytics practice.

This means we must learn how to align to business strategy and balance the needs, expectations and competing interests of multiple stakeholders.

Executives want business value as return on the organisation’s investments; operational stakeholders want results measured against operational KPIs; peer support functions (like IT, Finance, etc) want proof you’re worth their time, attention and allocation of their resources; and frontline workers want to know what’s in it for them.

Fortunately, we can take an analytical approach with each perspective by translating each into a set of well articulated questions.

Where to focus your time

Authors Piyanka Jain and Puneet Sharma of ‘Behind Every Good Decision’ offer ‘BADIR’ as a five-step analytics methodology for transforming data into insights.

Note how BADIR starts with a business question and ends with recommended actions. Also note what percentage of time is suggested for the steps.

BADIR model for learning analytics

Source: Piyanka Jain and Puneet Sharma, authors of ‘Behind Every Good Decision: How Anyone Can Use Business Analytics to Turn Data into Profitable Insight' (2014).

 According to BADIR, collecting and analysing data are only 20% of any analytics project; 80% of the time should be focused on business alignment (questions), people engagement (insights) and actions (recommendations).

This framework emphasises that business value and impact require not just data to insights, but insights to action.

From insights to impact

"There are a hundred things we could be doing. The key is to stay close to our customers – our human resource business partners and business leaders – to make sure we are doing the most impactful things" – re:Work interview with Guru Sethupathy, Capital One

I spoke with Visier data scientist and head of People Analytics Ian Cook about how we can ensure learning analytics makes the most impact.

Ian says impact requires securing other people’s buy-in. Why? The reason being is that L&D rarely has the authority to take the recommended actions on its own; so you must engage stakeholders not only for their support, but to compel them to take action.

To do this, you must clearly outline – then demonstrate – how making investments in workplace learning analytics will materially shift the business.

This approach will be new to them too; they’re not used to working with you in this way. A bit of change management will be required.

Given this, Ian suggests discussing the following with stakeholders to seek alignment, earn trust, build relationships and solicit their support:

  • What business, people or performance questions will you address using learning analytics?

  • What makes these questions worthwhile? Why are they worth addressing?

  • What impact do you expect data-enabled insights, explanations and recommendations to have?

Ian warns, “Remember to stay focused on what matters. Your goal isn’t to create the perfect algorithm, nor is it to earn a PhD. You’re trying to provide something of value to the business. That value is an answer to a business question at the lowest possible cost.”

This view is fundamental to both the short-term and long-term success of your learning analytics practice. At this early stage, you’ll need it to secure support and funding. At later stages, you’ll need this foundation to build future capability in years to come.

Next, start small. Iterate, hypothesise and test. Experiment and learn continuously. Focus on delivering value fast through quick wins.

By focusing on the ‘last mile’ from the very beginning of our learning analytics practice we can secure short-term and long-term support and investment.

Quick wins

Quick wins allow L&D to deliver value and build stakeholder trust and equity early in an analytics practice.

People analytics expert Jonathan Ferrar says: “Think small projects. Think projects closest to business needs. Think of today. Don’t spend too long on it. Working to identify the perfect solution and the perfect piece of work can mean it falls off the business agenda by the time you’re ready to report.”

Here’s a simple matrix to prioritise learning analytics projects into one of four quadrants based on business impact, time and cost:

Quick wins for learning analytics

[Adapted from Bersin by Deloitte May 22, 2017 “High-Impact People Analytics: The 'Recalculated Route' to Maturity“ by Madhura Chakrabarti, PhD and RJ Milnor]

Avoid projects listed on the left as they offer too little business impact to warrant investment.

Reject projects that offer low business impact at higher costs and time.

Select quick wins from the lower right. These are projects providing high business impact, at low cost, in a short amount of time.

Nimbleness, speed and agility count. Ideally, these early stage projects can be completed start to finish within a couple of weeks – no more than 90 days.

Use them to get good at articulating questions, refining insights and sharing results, improving with feedback, delighting your stakeholders and socialising a new insights-driven operating model for L&D.

Focus on the last mile

We can learn from failure. By focusing on the ‘last mile’ from the very beginning of our learning analytics practice we can secure short-term and long-term support and investment by engaging with stakeholders to address their people and business priorities.

Staying attuned to stakeholders’ evolving needs, priorities and expectations increases the likelihood of our analytical insights leading to actions – actions that provide the desired impact and business value.

 

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