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Effective evaluation and measurement of learning and development initiatives is critical to maximise the impact of training, identify gaps for improvement and ensure that efforts are aligned to the business' needs. <span class="a-text-bold a-text-italic">Learning Analytics </span>outlines how analytical approaches can respond to these challenges, the types and benefits of technological solutions and how to ask the right questions of organizational data in order to build a learning organization that boosts performance and competitive advantage.
Drawing upon case studies from organizations who have applied such approaches such as The Gap, Hilton Worldwide University and Seagate Technology, <span class="a-text-bold a-text-italic">Learning Analytics</span> will enable those involved in learning and development to make the business case for their activities and deliver an evidence-based service to their organizations. Alongside updated chapters on learning technology tools and moving beyond learning analytics to talent management analytics, this second edition also features new content on measuring informal learning, increasing data literacy, and framing L&amp;D's contributions through a portfolio evaluation approach.

Learning Analytics: Using Talent Data to Improve Business Outcomes

leadership

Leadership

Analytics

informal learning

training

impact

measurement

evaluation

margaret.parskey

learning and development

learning organization

gaps

improvement

business needs

performance

competitive advantage

case studies

analytical approaches

technological solutions

organizational data

evidence-based service

learning technology tools

talent management analytics

data literacy

management &amp; leadership

cindy.pinkstaffmiller

<div style="font-family: 'Segoe UI', Roboto, Helvetica, Arial, sans-serif; color: #333; line-height: 1.8; max-width: 850px; margin: auto; text-align: justify; font-size: 18px;">
<h4 style="font-size: 1.75rem; color: #1a1a1a; margin-top: 2.5rem; margin-bottom: 1.2rem; border-left: 5px solid #cc0000; padding-left: 15px; text-align: left; line-height: 1.3;">From Mastery to Fluency: The 30% Rule</h4>
<p style="margin-bottom: 1.5rem;">We often assume that to lead in a digital-first world, we need to go back to school for a degree in data science or computer engineering. In <b><i>The Digital Mindset</i></b>, Paul Leonardi and Tsedal Neeley dismantle this myth. They argue that leaders don’t need mastery; they need fluency.</p>
<p style="margin-bottom: 2.5rem;">The authors introduce the "30% Rule"—the idea that you only need about 30% fluency in technical topics to see the patterns, ask the right questions, and leverage digital tools effectively. For ELE members, this is an empowering shift: it moves the focus away from technical expertise and back toward what you do best—strategic leadership and talent development.</p>


<hr style="border: 0; border-top: 1px solid #eee; margin: 2.5rem 0;" />

<h4 style="font-size: 1.75rem; color: #1a1a1a; margin-top: 2.5rem; margin-bottom: 1.2rem; border-left: 5px solid #cc0000; padding-left: 15px; text-align: left; line-height: 1.3;">The Blueprint: Collaboration, Computation, and Change</h4>
<p style="margin-bottom: 1.5rem;">The book organizes the digital mindset into three core approaches that redefine how work gets done. For a senior leader, these are the levers of modern organizational performance:</p>

<ul style="padding-left: 25px; margin-bottom: 2.5rem;">
 	<li style="margin-bottom: 1.2rem;"><b>Collaboration:</b> This isn't just about using Slack or Zoom; it’s about "human-machine partnership." It involves understanding how to treat AI and algorithms as "team members" while maintaining a strong digital presence that fosters trust in a distributed workforce.</li>
 	<li style="margin-bottom: 1.2rem;"><b>Computation:</b> Developing a mindset for data means understanding where data comes from, how it is categorized, and—critically—what its biases are. It’s about moving from "gut feel" to "data-informed" by asking the right questions of the models presented to you.</li>
 	<li style="margin-bottom: 1.2rem;"><b>Change:</b> In the digital era, change isn't a project with a start and end date; it’s a permanent state of transition. This approach focuses on "adaptive learning" and creating a culture where employees are encouraged to experiment, fail fast, and iterate constantly.</li>
</ul>

<hr style="border: 0; border-top: 1px solid #eee; margin: 2.5rem 0;" />

<h4 style="font-size: 1.75rem; color: #1a1a1a; margin-top: 2.5rem; margin-bottom: 1.2rem; border-left: 5px solid #cc0000; padding-left: 15px; text-align: left; line-height: 1.3;">Why It Matters for the ELE Community</h4>
<p style="margin-bottom: 1.5rem;">Leonardi and Neeley’s work resonates with the ELE mission to prepare leaders for a complex, tech-driven future:</p>

<ul style="padding-left: 25px; margin-bottom: 2.5rem;">
 	<li style="margin-bottom: 1.2rem;"><b>Bridging the Talent Gap:</b> As HR and L&amp;D leaders, your job is to build a "digital-ready" workforce. This book provides a clear, achievable curriculum for upskilling that doesn't overwhelm employees but rather equips them with the confidence to engage with technology.</li>
 	<li style="margin-bottom: 1.2rem;"><b>Leading Through Ambiguity:</b> The "Computation" and "Change" frameworks help ELE members navigate the uncertainty of AI and Big Data, turning "digital exhaustion" into a competitive advantage through better systems and psychological safety.</li>
 	<li style="margin-bottom: 1.2rem;"><b>Redefining the L&amp;D Agenda:</b> It moves L&amp;D from being a "skills provider" to a "mindset architect," ensuring that digital transformation isn't just an IT initiative, but a fundamental cultural shift.</li>
</ul>

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<div style="font-style: italic; color: #444; background-color: #f4f4f4; padding: 30px; border-radius: 12px; border-right: 5px solid #cc0000;">As we navigate an era defined by data and algorithms, our most valuable asset remains our ability to think critically and act decisively. By embracing the 30% rule, we can strip away the intimidation of technology and reclaim our role as the strategic drivers of organizational evolution. The goal isn't to become a machine—it's to become a leader who knows exactly how to make the machines work for us.</div>
</div>

The Digital Mindset: What It Really Takes to Thrive in the Age of Data, Algorithms, and AI

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