Watershed

FEBRUARY 7, 2017

This week, we're spotlighting Andy Webb, director of training at Applied Industrial Technologies. In this post, Andy shares his experience and professional learning and development insights when it comes to the first steps to build and maintain a successful L&D program with learning analytics.

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Watershed

NOVEMBER 14, 2023

Every year, we look forward to running our “Measuring the Business Impact of Learning” survey. It’s an excellent opportunity to sense-check our thoughts on measurement with the views of frontline L&D leaders and professionals. As champions of using data to guide your people strategy, we relish the opportunity to explore the challenges, successes, and methodologies adopted across the industry.

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Watershed

OCTOBER 26, 2023

Our annual Measuring the Business Impact of Learning survey is now open. It only takes 5 minutes to complete and have your say!

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Watershed

OCTOBER 24, 2023

The rising importance of skills is unquestionable. Organizations face rapidly shifting landscapes, and the shelf life of both roles and technically-focused skills is shorter than ever. This shifting demand can feel like you’re forever chasing your tail.

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Watershed

SEPTEMBER 22, 2023

Are you attending DevLearn 2023 in Las Vegas? With so many informative sessions, deciding which ones to attend can be overwhelming. That's why we've compiled a list of our top picks to help you make the most of your time at the conference.

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Watershed

AUGUST 31, 2023

Our last blog post discussed how achieving a global view of your organization’s skills data is crucial in unlocking instant insights while being the bedrock for your future L&D Strategy. But to reap the long-term benefits, you need a reliable data foundation.

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Watershed

AUGUST 22, 2023

Let’s be very real. Gathering and organizing skills data from across the learning ecosystem is one of the most significant challenges facing learning leaders today. This process isn’t quick or easy, but it’s worth the effort.

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Watershed

JULY 26, 2023

As we continue to explore the role that learning analytics plays in the shift toward skill-based organizations, one small but important detail is emerging. A successful approach to data-driven insights requires vast swathes of reliable data. No surprise there, of course. But how do you get that information when you’re capturing the individual skills of thousands of employees across complex learning ecosystems?

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Watershed

JUNE 30, 2023

When you have tens of thousands of employees, you also have a lot of potential data and related sources about employee skills. So where and how do you get started? This blog post explains how L&D can access skills data from across a learning ecosystem to get a comprehensive view of skills and competency levels across the organization.

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Watershed

MARCH 20, 2018

After aligning learning evaluation goals, defining metrics, and designing your program, it's time to monitor progress toward learning program objectives.

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Watershed

JUNE 22, 2023

Let’s face it. One-size-fits-all training programs are a thing of the past. Welcome to the era of personalized learning experiences driven by data-informed insights. L&D's future is becoming increasingly intertwined with the power of skills data. So organizations must invest in gathering and analyzing skills data to stay competitive. But knowing where to find and start using skills data can be challenging.

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Watershed

JUNE 16, 2023

When I first started working in the learning space, I assumed that HR, talent management, and the world of L&D were all one and the same. After all, they share the same end goal of nurturing a productive, engaged, and skilled workforce. But dive a little deeper, and the reality appears a little different. HR and L&D events are often miles apart from the tech to the talk tracks.

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Watershed

DECEMBER 8, 2015

Kaufman's Levels of Learning Evaluation is one of several training evaluation models that builds on or reacts to Kirkpatrick’s model. This blog post explores the Kaufman method, including the two main differences that set it apart from Kirkpatrick's evaluation method.

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Watershed

JANUARY 6, 2016

Many learning evaluation models outline different ways of assessing whether our learning solutions work and why. It's the first step in ensuring our future learning solutions work. And as part of our learning and training evaluation series , this blog post explores Anderson's Value of Learning Model and its three-stage learning evaluation cycle that's meant to be applied at the organization level rather than for specific learning interventions.

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Watershed

MARCH 6, 2023

Most L&D professionals agree it’s essential to set aside a budget for learning measurement, but few are able to do so. Yet, organizations with a budget for learning analytics are more likely to believe in data and learning measurement, feel executive pressure to measure, and have learning analytics capability on their team.

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Watershed

MAY 25, 2023

Learning analytics supports learning and development in many ways. So how do organizations use learning analytics today? And how do they want to apply these analytics in an ideal world? This blog post explores findings from two L&D surveys to gauge how learning analytics is currently being used, and the metrics that sit behind measurement efforts.

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Watershed

MAY 15, 2023

Dancing robots, generative AI, and a focus on integrating skills into your learning strategy were all featured at Learning Technologies 2023. While we can write the dancing robots off as crowd-drawing distractions (along with the poor souls wearing full Stormtrooper and tiger outfits), it’s fair to say generative AI will be here to stay. Everyone talked about it, but how widely will L&D embrace it, and does anyone truly understand its impact yet?

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Watershed

MARCH 1, 2021

Is the learning record store (LRS) in your LMS or LXP providing the data and information you need to understand all the learning that’s happening across your organization? Or, are you limited to the data within that particular system? Remember, without a comprehensive view, it’s hard to know what’s really working and where your learners need support.

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Watershed

MARCH 6, 2023

Most L&D professionals agree it’s essential to set aside a budget for learning measurement, but few are able to do so. Yet, organizations with a budget for learning analytics are more likely to believe in data and learning measurement, feel executive pressure to measure, and have learning analytics capability on their team.

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Watershed

FEBRUARY 14, 2023

Implementing your learning analytics strategy requires people, technology, and budget. In this post, we focus on the people who create, organize, and evaluate learning analytics. Find out how many organizations have a dedicated learning analytics team, if their L&D department has analytics capability, and if they plan to change their learning analytics staffing in the near future.

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Watershed

FEBRUARY 7, 2023

Measurement, data, and benchmarking naturally go hand-in-hand. Many in L&D will instantly make the connection with how this statement could apply to either learner or program performance. But take a step back and you’ll realize the same principles apply when it comes to assessing your organization’s learning analytics capability. This blog post explores the results of recent survey questions on learning analytics maturity and capability.

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Watershed

AUGUST 24, 2016

Learning happens everywhere—from formal online compliance training to in-person training simulations and observations—and we simply can’t track all of it. That’s why you need to choose the most important blended learning experiences to target first and then tackle them one by one. From there, you can use tools, such as xAPI, to capture and track data from those experiences.

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Watershed

NOVEMBER 16, 2021

This blog series has covered L&D data requirements spanning a wide range of learning technologies commonly found in learning ecosystems. But there are so many other product classes we haven’t had a chance to talk about—until now. So, in this penultimate post of the series, we’re going to blast through several types of learning tools and technologies we haven’t covered yet.

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Watershed

NOVEMBER 10, 2021

Augmented reality (AR) and virtual reality (VR) are becoming increasingly mainstream modes of training—especially in industries that conduct training where real-world, in-person training is costly or risky, such as training with expensive equipment. Virtual experiences have the potential to generate huge amounts of data, as the head-mounted displays (HMDs) must track every movement as part of how they work.

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Watershed

NOVEMBER 3, 2021

We saw a massive and sudden movement from ILT to vILT during 2019 and 2020. But whether it’s virtual or in-person, instructor-led training represents an important mode of learning for many organizations. The personal human interactions of instructor-led training do not lend themselves to digital tracking as easily as e-learning or video content, so how do you track them?

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Watershed

OCTOBER 27, 2021

Organizations are increasingly relying on data to make informed decisions and maintain a competitive edge. This trend isn’t limited to a particular region, industry, or business size. Whether it’s a local grocery store ensuring their shelves are properly stocked or a Fortune 100 organization creating a global transportation plan, data plays an integral role in our daily lives.

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Watershed

OCTOBER 7, 2021

Business intelligence tools and learning analytics platforms are complementary products that process data and provide reports and analytics to different audiences and for different purposes. BI tools are generally used by your data team to generate reports requested by the business, whereas a learning analytics platform may be used by the learning team and by operational managers to keep track of their learning, learners, and programs.

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Watershed

SEPTEMBER 29, 2021

One of the key benefits of a learning analytics platform is the ability to easily combine your organizational data with your learning data so you can filter by and compare different organizational units. This combination of data also means you can give operational managers access to reports, using data permissions to ensure they only see data about their own people.

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Watershed

SEPTEMBER 22, 2021

DevLearn is one of the biggest conferences on the L&D calendar, and after a digital-only conference last year, we’re excited to be attending DevLearn 2021 in person! Sadly, due to COVID-related travel restrictions, I can’t be there in person, but our booth (609) is right next to the main entrance. Bill, Craig, Stephen and Izzy will be there, and we’d love it if you popped by to say hello!

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Watershed

SEPTEMBER 8, 2021

We’ve been exploring how to define data requirements for learning analytics —including the questions and considerations to discuss with vendors when connecting platforms to your learning ecosystem. In this blog post, we’ll focus on why a robust data integration is critical when it comes to badging and credentialing software. We’ll also explain how you can extract that data so you can combine it with other L&D data and report on it in a learning analytics platform (LAP).

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Watershed

SEPTEMBER 1, 2021

Surveys are a vital tool in the learning analytics toolkit, capturing the learners’ ratings and feedback on training and more. This data is most valuable when reported alongside data about the learning itself, but how do you get that data out of the survey tool in the first place? This post explores the data requirements you should look out for when extracting data from a survey tool into a learning analytics platform.

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Watershed

AUGUST 25, 2021

Having explored data requirements for the central systems of a learning ecosystem , the LMS and LXP, let’s turn to the products you might bring into your ecosystem to enhance those core platforms with additional functionality. Video platforms turbo-charge your training capabilities and can generate a lot of useful data about what learners are watching—right down to the level of where they’re pausing, skipping, or rewatching.

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Watershed

AUGUST 18, 2021

So far in our data requirements blog series , we’ve explored how data from the learning management system (LMS)—the heart of your learning ecosystem—can be brought into your learning analytics platform (LAP) for analysis. Well, if the LMS is the heart of the ecosystem and the LAP is the brain, then the LXP is the smiling, happy face that welcomes learners as well as the hands that point them to the learning experiences most suited to them.

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Watershed

AUGUST 11, 2021

Our data requirements blog series explores the data you might collect from the various tools in your learning ecosystem, how you might get that data out, and what questions it might answer. In this post, we’ll look at one of the most critical platforms in your learning ecosystem—the learning management system (LMS).

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Watershed

AUGUST 2, 2021

If you want good, comprehensive reporting that answers all your questions, you need good, comprehensive data. But when you have multiple tools, systems, and platforms across your learning ecosystem , how can you ensure you’re getting all the data you need and in the proper format? In this blog series, we’ll explore data requirements for the various tools and technologies that are commonly found in learning ecosystems as well as requirements and best practices for extracting data from each system

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Watershed

JULY 13, 2021

The Watershed team is mainly based in Nashville, Tennessee, but there are a couple of us on the other side of the pond in England. There’s been a lot of excitement over here the last few weeks as the England soccer team (we call it football) have been doing uncharacteristically well in the postponed-due-to-COVID Euro 2020 Championship. England reached the final against Italy and, despite not being a huge sports fan, I decided to watch the match and cheer them on.

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Watershed

APRIL 28, 2021

So far in this series, we’ve explained the differences between internal and external learning record stores , how xAPI conformance affects reporting, and data extraction methods. Now, we’ll wrap things up as we mash together all the bits we’ve discussed during the past four blog posts and look at how the LRS can play a role in the larger data ecosystem.

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