Morris Chang

“Without strategy, execution is aimless. Without execution, strategy is useless.”

Why you need a data strategy for L&D

We have the privilege to live and work in an extremely fast changing and demanding business environment. The pace of technology development is growing. Most (if not all) companies are going through a digital transformation, and corporate HR/L&D has a crucial role to prepare the workforce for the future. No wonder that the need for L&D to demonstrate impact is higher than ever. No wonder that the number 1 skill for HR and L&D is Analytics. But before you enter the fascinating world of learning analytics, you will need to build and implement a solid learning data strategy first.

We work and learn (and live!) more and more in the digital space. With each digital activity we do, we create data. That is why we are creating more data than ever before in history. The key reason to have a learning data strategy for me is the opportunity to unlock the enormous value of learning data by harvesting, analyzing and using that data to continuously track and improve the way we support our organization in personal and business development.

There are, however, some additional benefits. A learning data strategy allows L&D to more structurally integrate performance & business data to identify, analyse and quantify development needs and demonstrate business impact of learning programs.

A learning data strategy will enable L&D to talk ‘data’ with business stakeholders. In a company that is going digital this allows you to talk the language of your business customers and improving the credibility of L&D. It will also improve the quality of learning data, which will benefit the employee experience as it improves the ability of employees to find relevant learning content and will improve machine learning and AI based recommendations. Finally, as data and analytics skills are among the key future skills, a data strategy will help L&D to start building future proof skills and capabilities in your own organization.

What is a learning data management strategy?

According to the global Data Management Community body of knowledge, a data strategy “describes a set of choices and decisions that together, chart a high-level course of action to achieve high-level goals”. The Data Management Maturity Framework of the CMMI Institute defines the purpose of a data strategy as “defining the vision, goals and objectives for the data management program, and ensures all relevant stakeholders are aligned on priorities and the programs implementation and management”. As with every discussion on strategy there is no one single right answer and there’s a wide choice of strategy definitions, documents and templates online to choose from if your need one. So, I’m sharing my view based on one of the experts I am following. Bernard Marr is one of the world’s leading experts on data strategy and author of many books (including one on ‘Data Strategy: How to Profit from a World of Big Data, Analytics and the Internet of Things’) and articles on the topic, so I will use his “7 points every business should include in their data strategy” to ‘translate’ to the domain of L&D:

1. Align your learning data strategy with your learning strategy

Assuming you have a learning strategy that is aligned with your business strategy (if not, I suggest you do!), the next logical step is to define how data can support your learning strategy. You could think of any (and even all) of the following examples: If your L&D strategy is to be highly efficient, you will want to focus your data strategy to track and monitor efficiency in terms of usage of programs, or costs per delivered training hour.

If you have a very customer focused L&D strategy, your data strategy should consider tracking customer demand and quality of the customer experiences. Think how web shops use Google analytics to identify what people are looking for and if they have a positive online shopping experience. It could mean using data to decide what online training opportunities you keep or get rid of. It also means having high quality data to ensure employees can find relevant training, and get meaningful suggestions from the LXP or other machine learning algorithms. If your L&D strategy is very much focused on leadership development, you should also focus your data strategy on this topic.

As data can be used for many different purposes, this first step includes setting priorities; you cannot do all, so select 2-5 area’s where you want to focus on. For each area you will also need to identify the potential gains of having a solid and structured data management strategy in place. This can be anything from reducing risk of non-compliance, to speed of getting the right data on the table to make decisions, and better quality of data to make better informed decisions.

2. Identify areas where you can achieve short term results.

As I have shared before, the domain of data management can be quite conceptual and vague for many people. That is why I feel it is important to make things tangible as soon as possible. In one or two of the strategic area’s defined in point 1, identify a quick win that you can use to demonstrate the value of having a data strategy. This is where your learning data strategy will first touch learning analytics, as you will mostly need some (simple) analytics to do so.

Interesting investigations could be on where in the organization people consume most (formal) training, or the top 10 most popular non-mandatory courses (in my experience, people love top 10s!). Most likely these quick wins use data from your LMS as that data is readily available and (fairly) easily accessible.

3. Data inventory and Requirements.

Now the fun bit starts. You will be amazed how many people have told me that they want to do analytics, but they do not have the data. This is exactly why you need a strategy: to define what data you have, what data you need and if there are gaps (which is mostly, if not always, the case). And you need a plan to start capturing the missing data. For each of the focus area’s mentioned in point 1, you will have to map this out. I’ll use the above examples again. If your L&D strategy is all about efficiency and you have defined your key KPI as ‘total cost per delivered training hour’ you will need standardized data on costs. In this exercise, do not just consider costs related to classroom delivery or elearning development, also include salaries in L&D, tools and technologies and even costs associated with travel and time away from work while employees take the training. If you do not have all of this in place, you will have to come up with a way to start collecting this data. The reason this is interesting is that most likely this is the moment you will have to start looking beyond the domain of L&D. If you want to define the impact of leadership development programs, you will have to get data from other parts of HR. Think of 360’s or people surveys, people performance data etc. If you want to demonstrate the impact of L&D on business performance (don’t we all?), you will have to start collecting business performance data.

4. Data Governance

Data governance for me means to have processes, standards and methodologies in place to ensure that data is used consistently, correctly and has the right level of quality. The consistent use of data, or in other words making sure that everybody has the same understanding when it comes to the purpose and definition of each data field, cannot be underestimated. If you want to report out on all mandatory training in the company, you will need a single definition of what mandatory training actually is. If you want to measure the uptake of social learning in the same company, you will need a clear definition of what social learning is.

A second key element of governance is around data quality. Who is responsible for the quality of data? Who is checking? What happens if people make errors? Cleaning up poor quality data can sometimes take 80% (!) of the time of highly specialized and hard to find data analysts (who also really do not like to clean up other people’s mess, so you run an additional risk they will go somewhere else). So data quality is important. Understanding who is responsible for quality and actively track the quality of your data is key.

The final part of data governance I want to mention is data security and data privacy. You cannot capture and use data anyway you want, so make sure that you fully understand all legislative requirements around security and privacy. If this is not considered carefully the potential cost for the company in terms of fines and brand image damage can be huge.

5. Technology

The technology space of data & analytics is a fascinating and fast-moving world. Recently was introduced to a tool called Orchestra that claims to have the potential to collect and manage all data in your company. Not just learning data, not just HR, but everything from customers, suppliers, products and services, finance, you name it. Their key promise is that when everything sits together, you can better manage it, better report on it, and better mine/harvest the data to create value in ways we never imagined before, because we never had all data in a single place. The tool is owned by Tibco, which is also the company that owns Spotfire, a data analytics and visualization tool that I used at the Shell Learning Strategy team to create global learning compliance dashboards as well as dashboards on global training consumption and course utilization. At Philips we used Qlik and for one of my current customers, I am using Microsoft Power BI. There is simply so much technology out there, it can be very tricky to select the technology that is right for you. You may be able to use your LMS or LXP for some of your data collection, processing and reporting, but the moment you start to connect learning data with other data sources, I find that most learning tools are not able to handle this. This means you will have to start thinking of additional tooling.

My most important tip: Do not underestimate the value of MS Excel! It is still by far the most widely used data & analytics tool out there. It’s flexible and has massive functionality available. So before you go out there and buy an expensive fancy tool, just try it!

Also if your company is already doing a lot of data and analytics as part of their core business…go and talk to them and seriously consider using the same technology they have. It will help you greatly with the next point: Knowledge and Skills

6. Knowledge and Skills

Working with data, even in the context of learning program design and development (what title, what key words, what is the duration of the course?) does not come naturally with most people in L&D. On the other hand I would also argue that most data analysts and scientists are not very familiar with the L&D domain. That means that we will have to develop the capability ourselves. Many companies still struggle with data and analytics in general so this is not an easy job. But it can be done and we’re lucky because we are the experts in developing new skills! Right?

Here are some tips:

  • Make sure that your L&D leadership team is fully convinced of the importance of a data strategy.
  • Fully utilize knowledge and skills already available in other parts of the company.
  • Start small -> create success and/or learn from mistakes -> and build on that.
  • Get external expertise in if you have the means to do so (at SLT Consulting we offer both training on data & analytics in Learning & Development as well as advise to help you define your own data strategy, so we’re not fully neutral here!)

7. Just Do It.

As a last step of your strategy, it is time to build the plan and think of how you want to manage the change during the implementation. What activities are scheduled and when, who owns what activity, how do you get everybody on board? And what is required in terms of effort and investment to fully implement the strategy.

To wrap up this blog, some final tips:

Make sure that you update your strategy on a regular basis. Priorities could change. The context we work in (be it the market your company is operating in, your company strategy or L&D strategy) most likely will change over time.

Don’t forget, there’s quite some resources available online to help as well. I like using the Business Model Canvas for many things, including strategy building. Also Bernard Marr has a very nice template freely available here. And if you cannot find what you are looking for, you can always contact SLT Consulting!

Building a Data Strategy for Learning & Development

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