Thursday, 09 November 2017 03:16

Three Priorities for Every Data-Driven Leader Featured

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A few years back, “big data” was all the rage. Today, you may be more likely to hear “data analytics. The bottom line remains the same: You have to change yourself, your team, your way of operating and — most importantly — your strategic approach to doing business with stakeholders.

To do this, you must become a data-driven leader committed to learning the basics. You can’t walk the walk until you can talk the talk. Then, find and nurture allies. A successful data analytics initiative requires friends in high and low places. Finally, reassess the profit and loss statements (P/Ls). Changing your approach to data starts with changing your mindset, which starts with the key performance indicators (KPIs) that you measure outcomes instead of activity.

THE STATE OF DATA TODAY

Statistically speaking, you’re likely at or near the beginning of your data analytics journey. But it’s time for change. In 2016, 54 percent of companies had a chief data officer, up 12 percent since 2012. And they have a key seat at the proverbial strategic table. In contrast, the 2017 Bersin Learning Organization Maturity Model, which tracks companies at four levels of L&D maturity, tells a very different story about our use of data. Thirty-five percent of companies surveyed are in the bottom tier, Level 1. They are still focused solely on traditional metrics like feedback from learners, stakeholders and follow-up assessments.

At Level 4, the Bersin model’s top tier, it’s a totally different data universe. Companies are collecting new data while utilizing existing data to improve development and work. Bersin’s findings on the implications for their businesses are pretty compelling. These organizations score better on performance improvement, information architecture, knowledge management, human factor design and content curation than less mature peers. And, perhaps most importantly given how rapid technological advances are changing work and society every day, these companies can look ahead the future and ready employees to adapt to change. But they’re only six percent of companies in the study.

RISKS OF IGNORANCE

What’s so wrong doing things the way you’ve always done them and not aspiring to data maturity? In short, by not leveraging data analytics or doing so without the right guidance, L&D organizations severely limit their ability to solve problems and advance business strategies. That’s what makes them order takers instead of valued partners.

Other more fundamental risks to watch for:

>>  Decision-making by gut, not fact

Common sense can sometimes be our enemy, because sense and logic can be deeply personal and subjective. Data, however, can remove guesswork, biases, anecdotal reasoning and other human foibles that can throw strategic efforts off course. Data can also take the emotion out of business discussions and break down silos as objective metrics light the way forward.

>>  Solving the wrong problem

You’ve surely been there — weeks or months of effort to resolve a vexing challenge are revealed to have been a waste of time, resources and goodwill, because the challenge turned out to be a misunderstanding, a red herring or a rush to judgment. Data helps avoid predetermined (and often erroneous) approaches to problem solving.

>>  Measuring efficiency  rather than effectiveness

Your team may take pride in having filled all available seats for your latest learning endeavor. But is your company better served by getting “butts in seats” or by ensuring that those employees are learning the right content at the right time in a way that drives the intended results? Even the most advanced L&D organizations on the planet can benefit from revisiting the metrics they’re capturing to ensure a focus on effectiveness and not just efficiency.

Too many companies, and L&D functions, don’t focus on defining and achieving measurable outcomes that align with and advance business strategy.

YOUR ACTION PLAN

Here are three very straightforward actions you can take to advance on your journey as a data driven leader.

1 First, start with learning the basics.

You won’t get very far if you can’t speak the language and follow along in conversations. You don’t need to become an expert, but it’s crucial that you read up and get with the basic parlance.

Information without interpretation has little value. You or a member of your team may not be running the numbers, but analytics requires business understanding to give it meaning and power. It’s relatively easy these days to “buy” the services of a data statistician. What you can’t buy is someone who knows your organization and can ask the right questions.

Start with the four types of analytics. Data analytics is commonly categorized as descriptive, diagnostic, predictive or prescriptive. They are separate from, but roughly align with, Bersin’s four levels of L&D maturity.

a.  Descriptive analytics asks, “What hashappened?” Mining data to provide trending information on past or current events provides decision-making guidance for future actions, often in the form of key performance indicators. Descriptive analytics data is usually displayed within reports or dashboards, which are sometimes automated to issue alerts or trigger actions at various thresholds. In day-to-day business operations, much of analytics is descriptive in nature.

b.  Diagnostic analytics asks, “Why has this happened?” Utilizing statistical and analytical techniques to identify relationships in data sets and degrees of correlation between variables helps pinpoint the causes of problems and formulate corrective solutions.

c.  Predictive analytics asks, “What could happen?” The term encompasses a variety of techniques, such as statistics, modeling, machine learning and data mining, which are used for finding cor-relations within big sets of current and historical facts, to make useful predictions about future events.

d.  Prescriptive analytics asks, “What should we do?” It explores a set of possibilities and suggests optimal course(s) of action based on descriptive and predictive analyses of complex data. Utilizing advanced analytical and mathematical models, it can also provide reasons for its recommendations and possible implications of following them.

The best partner for a data scientist is both knowledgeable about the business and relentlessly curious about what makes it tick. This type of person knows how to probe for understanding and judge whether data “feels right.” Deep knowledge of your company, combined with data analytics prowess, is a winning combination.

2 Find and nurture allies.

If there’s one immutable law of data analytics, it’s that you cannot do it alone. Reach out, within and outside your company, to professionals who are successfully using their data; take them to lunch and ask lots of questions.

It’s especially important to identify key data players within your company or non-profit: the data experts, gatekeepers and evangelists, whether in I.T., a data-savvy group like finance or marketing, or on the board. There are a few reasons for this. First, you may encounter leaders who re-sent both you and the very notion of data analytics. As that kind of resistance demonstrates, moving to a data-driven leadership culture, like any change effort, will bring out the best in some people and the worst in others. Some will instantly grasp its meaning and potential, while others may be skeptical, cynical or worse. It’s important to find allies early, as detractors may be frequent and fervent.

Another reason to seek allies is practical. Most L&D organizations lack the experience and clout to single-handedly lead a data analytics change effort, especially if it requires data from outside your function. Building strong relationships with leaders from one or more lines of business (such as sales, marketing or operations), you can gain:

a.  Understanding: These functions tend to already be engaged in data analytics and thus have familiarity and resources valuable to an analytically-aspiring L&D team.

b.  Access: Teams already heavily using analytics are likely data gatekeepers whose cooperation (and data) you will need to be successful.

c.  Advice: Analytics-minded executives can help focus change efforts on concrete, measurable business outcomes, avoiding potentially narrower, L&D- focused issues (although it’s generally advisable to start small, you’ll do well to think beyond L&D to all of your company as you become a strategic, data driven leader).

3. Reassess KPIs.

The third priority is an underlying mindset shift. Data analytics is a means to an end: improving your team’s performance. But that can only happen if you are measuring the right outcomes. Are you capturing efficiencies only, or also effectiveness? What have you always wanted to measure? Once you start to look at measurement in a different light, you’ll likely be motivated by the new potential you see to prove to yourself and your stakeholders that what you do matters and advances organizational strategies.

The first mindset shift is to use data to measure outcomes rather than activity. Mature organizations collect more data at more frequent intervals from more sources and are therefore better at understanding their organizations and what they need in order to make work better, and to utilize metrics and data sources that measure results of actions and not just the actions themselves.

Let’s look for a moment at so-called “rear-view mirror KPIs”: what happened. A classic example is using learner evaluation scores as evidence of impact. Yet when my team looked more closely at this a few years ago, our research showed that sales training survey results were typically driven by room temperature, food quality, and whether the presenter was funny. There was no correlation between learner feedback scores and sales rep productivity.

Assessing whether the course achieved its defined goals and objectives requires an entirely different, and more sophisticated, set of questions and measures but will enable learning teams to objectively demonstrate to their stakeholders and themselves that their efforts positively impacted the business.

L&D professionals who are measuring rear-view mirror KPIs have simply been doing their job as they were asked to do it, aiming to fulfill the expectations of their internal customers. This brings me to another critical mindset shift required to change you from an order taker to a strategic partner, and it’s yours.

L&D leaders must take the initiative. We must not wait for business stakeholders to change their expectations of us. It is up to us to hold our executives accountable for defining desired business outcomes — and have them hold us accountable for tracking our impact on those outcomes.

YOUR NEW END GAME

Achieving these priorities and especially these mindset changes are the critical first steps toward measuring impact instead of activity.

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