The Decision Economy

Unleash Training Intelligence for Data-driven Decision Making

Enterprise training sits in the epicenter of organizational change, making training data one of the most immediate and valuable strategic assets for critical decisions.

Illustration of various types of training data as a rainbow of colors being focused through a prism to create momentum.

The days of limited activity metrics—like attendance, exit surveys, and course count—are over.

Enterprise training has become a sophisticated locus of talent management innovation, driving business success. Among training teams in leading organizations, the accessibility, analysis, and utilization of a well-crafted data architecture fuels and informs this innovation, not only for the training function but for the success of the business as a whole.

In this guide, we’ll discuss the significance of data literacy, as well as the risk of failing to pursue this core skill for training leaders today. We’ll identify three myths about training data management that hold back training teams from realizing their full impact in the organization. And, we’ll outline how to architect your plan for mining decision-ready from the training function, transforming training from a cost center to an intelligence hub for your organization.

Researching how training can enter the decision economy is a powerful first step in putting your training data to work as organizational intelligence. Let’s get started.

Part 1

Data Literacy & Training

Why Leading Enterprise Training Teams Must Level up Data Fluency

Data alone doesn’t drive decisions. Your data-grounded insights do.

Data literacy is a learned skill that provides the ability to interrogate, understand, and communicate effectively with data. It includes critical thinking components that facilitate the analysis of data, and communication skills that make it possible to tell your story using data.

Team meeting in a modern office with a woman gesturing at a screen that has charts with a clicker.

Every business leader today knows that data utilization is important, but the urgency felt by training leaders for adopting this expertise increases when the risks of failing to leverage training data well are considered.

The risks of weak data literacy for training include:

  • An inability to demonstrate the ROI for training, leaving budget and key project sponsorship at risk, despite growing demand driven by workforce changes.
  • Isolation of training insights, limiting the leverage of this institutional evidence to talent management alone instead of the full scope of business impact.
  • Defaulting to reactive training tactics that merely respond to business needs that have already created a pressure on the business rather than formulating proactive strategies that anticipate training needs and the power of learning to increase performance.

The State of Data Literacy in Enterprise

If your organization is just beginning to implement data literacy, you’re not alone. Despite a decades-long focus on data acquisition, Americans rank toward the bottom of a global survey on data literacy. A report from the National Center of Education Statistics (NCES) surveyed the data literacy of working age adults. America ranked 21st out of 23 countries participating.

Despite the fever-pitch focus on the importance of data in business, the needle for data mastery hasn’t moved that much in recent years. A 2020 Forrester report found only 40% of employees feel they have the data skills required for their role. This is despite the fact that the same report shows 82% of leaders expect all employees to have basic data literacy and 70% of employees are expected to heavily use data by 2025, up from 40% in 2018.

82% of leaders expect data literacy 70% of employees expected to require data literacy 40% of employees have adequate data literacy

Learning Technology and Training’s Struggle for Improved Data Utilization

As has been true in every corner of the enterprise organization, the conversation on data literacy within the training function runs parallel to the evolution of the technology that serves the mission of learning and development.

Perhaps more lagging than other mission critical areas, training has sustained a large gap when it comes to operational technologies and technological investment. This lack of investment has meant a lack of accessibility to collective, coherent data models and the resulting delay of the opportunity to develop data competency among staff.

The data utilization impact gap can be measured in dollars. A 2018 IDC study reveals that enterprise-scale companies invested trillions in key projects aimed to update their business, but 70 percent of these projects have failed because technology investments accelerated without considering data literacy among teams impacted. Commonly, the relentless focus on data acquisition has stranded many enterprise teams, including training, with a wealth of data but meager options to analyze or act upon their findings.

Investing in data literacy is the first step to remedying analysis paralysis. The investment doesn’t need to be huge, a simple change of mindset and willingness to politely interrogate data is a great start.

BREAK IT DOWN

Data Literacy Shares Your Impact

A training team that is data literate can:

  • Ask the right questions to interrogate your data.
  • Understand which data is relevant.
  • Conduct tests to prove the validity of the data.
  • Interpret data into useful and meaningful results.
  • Visualize data to quickly communicate your impact.
  • Tell a story with data to engage and convince stakeholders.

BRING IT TOGETHER

Always Interrogate Your Data

Adopting a curiosity about data is the cost of data literacy. Consider these questions, which should be asked as a matter of course.

  • How important is this decision?
  • Will this decision only serve the training function, or the organization as a whole?
  • What data do we have, or can acquire, that supports or challenges this idea?
  • Have we tested this result/data? What is required to be confident in this data?
  • What further evidence do we need to act on this data?

Data Literacy: Competitive Advantage for ForgeRock

The second largest repository of data for ForgeRock, one of the leaders in identity management, is their training data.

Click to read the ForgeRock story.
Administrate is all about slick administration. When Sun Microsystems was at the height of its growth, around 2000 or 2001, I looked at the number of staff we had to deliver the same amount of content to the same number of students, and it was 10x the number of staff that I have globally now. To do the same job.
Kevin

Kevin Streater

Vice President of ForgeRock University

Part 2

Training Data Myths

Eliminating Common Assumptions That May Be Blocking Data-driven Decision Making

Two business professionals looking at spreadsheets and charts on two monitors.

Training has always collected data, but has seldom driven it.

Always, in defense of tight budgets and limited time, training teams have focused on capturing high-level data on learner and program performance. These descriptive analytics maintain foundational importance when understanding the value of training and the measure of this key organizational investment. While these numbers are important, they are limited in their ability to invoke deeper insights into future needs or immediate opportunities for business wins.

Where analysis of training data does take place, it is frequently dependent upon spreadsheets that require manual effort to maintain but provide little value to the organization. It can be difficult to establish data correlation across training tools themselves, let alone relate to larger organizational KPIs.

Evolving your ability to harness training data will require change. The first change is in your organizational mindset about the data itself. What assumptions or limiting beliefs are present within your organization that are hindering your ability to grow toward data-driven decision making for your program and your organization?

3 Common Myths About Training Data


1.
The Myth of Excess:

“We have a lot of reports already.”

Businessmen in a meeting gesturing at a tablet with charts.

Volume is not the sole determinant of value when it comes to data. If your program is like most, you are using anywhere from nine to 12 disparate systems or software to plan, produce, deliver and report on your training program.

Each of these tools is producing data points. It is easy to get lost in the assumption that you do have the data you need because the tool offered you some numbers. However, if you’re using pre-programmed reports embedded in the tool, chances are that the output is more aligned to the tool’s marketing pitch and value proposition than it is to the impact of your program on your business. Do you have data that actually reports on your program, or data that reports on your tools? There’s a difference.

2.
The Myth of Access:

“There is no way for us to get the data that we really need.”

Meeting where business professional gesturing to laptop while a doctor and his colleague look on.

Like many good stories, this myth resonates because there has been some truth in it. Until recently, it has been difficult to imagine a way to create a holistic data architecture and reporting alignment of the training function.

In fact, this need is largely responsible for the emergence of training management platforms, including Administrate. Because training touches knowledge, skill, experience, compliance, and a multitude of intellectual and physical resources, it is imperative that 100% of your training data be accessible and reportable. Now, that access is possible. Achieving this level of access may require you to think differently about creating a learning technology infrastructure for your program—not unlike the similar progression of operations toward ERP systems. If training operations platforms are new to you, take time to learn about the possibilities they offer before you settle for the limitation of included reports.

3.
The Myth of Isolated Impact:

“Training data is primarily about the training program.”

Assembly line worker in a factory.

Many organizations have outgrown siloed thinking, but few have operationalized beyond it. With workforce sea changes like “The Great Resignation” and the still resolving question of distributed teams versus hybrid versus in-office work models, never has it been more apparent that the training team is a vital function not only in the sustainability of the entire organization but also in its ability to remain agile and competitive. Expanding that confidence beyond the function of training to training’s data is the crossroads where many leading organizations now find themselves. They know training is strategic, but how do they interrogate that data to mine the beneficial business intelligence that it offers?

Training leaders are embracing this new role of business intelligence and equipping their teams to provide analysis and insights beyond the former up-level reports. They are providing forecasts of business impact based on learner results gathered and connecting this information to production capacity, scheduling, and more. Talent retention strategies include learning and development as a key stakeholder as candidates, many of whom anticipate changing careers three to four times in their lives, value training as a benefit on par with 401k investments and health savings accounts.

Connecting the valuable organizational data that training offers via diagnostic analytics is the first step to dispelling this myth. Once you can show how training impacted specific KPIs throughout the organization, you can demonstrate how training data is relevant for other functions. From there, predictive and prescriptive analytics can be leveraged to shape strategic decisions for talent, production, finance, and more. Breaking training data out of isolation requires adding context to that data.

BREAK IT DOWN

Dispelling Data Myths Gives You Influence Over Strategy

By dispelling these training data myths you:

  • Show training’s value to the organization as a decision-leader.
  • Boost training ROI by connecting outcomes to bottom-line performance.
  • Lead the conversation around technology investment, not struggle for additional budget.
  • Lay the groundwork for building an advanced, data-driven training operation.

BRING IT TOGETHER

Mindset Shift and Tech Investment

These ideas will help you dispel these myths:

  • Understanding who can benefit from training data, and why.
  • Evaluate the data you have, make sure it is valuable and useful.
  • Consider replacing technology that produces too many data points, or pre-made reports with a more mature solution.
  • Master and apply the concept of learning analytics to your training data.

Boston Whaler Reveals Organizational Value in Training Data

In eighteen months, Boston Whaler needed to double the production of their factory and launch several new boat models, which meant increasing the physical size of their factory and doubling their headcount.
To accomplish this, the entire management team worked together to invest in a training platform that could support a large intake of new employees and train on the construction techniques required for their new boat models. While expanding, they also needed to reduce manufacturing errors and involuntary employee turnover, and by marrying their training data with metrics from their factory production systems, they could pinpoint when and where errors were happening and intervene with timely instruction.

Click to read the Boston Whaler story.
“The turnover report we’ve built within Administrate helps us track turnover, automatically, every 30 days all the way to every 365 days. This helps us identify stresses and causes of turnover. It also allowed us to pinpoint exactly when our highest turnover was taking place.”
Brandon Beck, Vice President of Human Resources at Brunswick Corporation

Brandon Beck

Vice President of Global Talent

Brunswick Corporation

Part 3

Architect Decision Analysis

Using Operational Constraints and Requirements to Accelerate Data-driven Decision Making

Business professional presenting reports to team.

Combine training data with operational requirements within a training operations platform to execute data-driven decisions.

Training teams that want to participate in the decision economy need to tell their story through data, connect training data to larger organizational goals, and automate their decision making. Even highly data-fluent teams, equipped with the most reliable information can still fail to make accurate, and repeatable, decisions. Why? Many overlook the secret to decision analysis hiding in plain sight: operational requirements.

Training Operations: The Root of Decision Analysis

You may not think the operational requirements that drive your daily training programs are also key to data analysis, but they are the exact inputs that help technology automate many types of decision making for you.

Imagine how a quarterly training event calendar comes together: weeks are spent collecting requirements from across the organization, dozens of calendars are consulted, whiteboards are scribbled with notes about instructors, classrooms, or equipment, and your training team spends late nights hashing out the nuances of conflicting schedules. It takes weeks, maybe a month.

These whiteboard notes and coffee-fueled ideas about resource constraints are inputs that add context to data, and ultimately help automate decisions around complex training logistics.

Scheduling a calendar of events is just one example, your team is deep into these operational quagmires every day. All of them are opportunities for decision analysis.

Identify Operational Requirements to Drive Decisions

By tracking operational requirements, you can understand the scaffolding of decision making as a process. For example, by knowing your instructor’s calendars, you can cross reference a classroom calendar and only schedule that instructor into classrooms that are available.

That is a very simplistic decision, not one likely to change your organization, but when you scale such a simple decision across your entire training function, the manual effort this requires becomes a true cost to the enterprise.

Now, layer on more requirements to this simple scenario. What if data reveals this instructor performs well with certain cohorts? What if those cohorts have to meet regulatory requirements for specific training by a certain date, throwing the original training calendar into disarray?

Sure you could train these cohorts using a different set of instructors, but their performance may drop. How do you balance this scenario for the best possible outcomes? With regulatory requirements in play, this seemingly mundane choice could impact the entire organization.

These are all decision-points that contribute to arriving at a final choice.

BRING IT TOGETHER

Operational Requirements Drive Decision-making

The cost for operationalizing decision making is fairly cheap: these questions interrogate your training operations and reveal requirements to drive decision making. Your team can likely answer these questions very easily.

  • Do you have enough resources to ensure a training strategy succeeds? If not, where are you falling short?
  • Which team members are required for a particular task or project? What are their unique roles and responsibilities? How many pertinent details are in their head that need to be documented?
  • What courses are needed to solve a particular problem? What are the components it takes to create that course?
  • What tasks are required from a learner in a particular course? What about the instructor? Training manager? Instructional designers?
  • Is there a specific order for associated tasks within a course? Within a learning path?
  • How do you measure success for this course?
  • Who are the stakeholders for this course/ who cares about the success of this course?
  • How are communications with learners and instructors resolved?
  • Can you automate any portion of a strategy? If so, how much time will it save? How reliable is the automation? How much manual effort does it still require?

Investigate a Training Operations Platform for Rapid Decision-making

Administrate helps enterprise training teams make rapid decisions and simplify logistics by combining training data and operational requirements.

Businessman using the calendar feature in Administrate on a laptop.

A new class of learning tech is helping training teams catch up to the data-first technologies that have transformed other functions, such as sales and marketing. A training operations platform is software infrastructure for training which acts on complex data to solve multivariate needs. A training operations platform makes it possible to:

  • Forecast learning demand.
  • Quickly identify resource constraints.
  • Understand how specific activities create momentum in your organization and which modality works best for specific targets.
  • Create agility to meet rapidly changing business needs and priorities.
  • Push training insights to your organization instead of relying on pop-up demands or directives to determine program evolution.
  • Leverage training as a key asset for employee engagement and retention by maximizing training time, modalities, and opportunity within resource limitations
  • Easily and quickly comply with audit requirements and reporting needs

Our platform, Administrate, is a leading learning tech infrastructure for enterprise. Administrate unifies all of an organization’s existing learning tech into a single interface, sharing data and working together more efficiently to automate many training operations including many types of decision analysis.

Partnering with Administrate allowed us to bring more robust data collection and reporting to our internal operations. We’ve improved our reporting capabilities, our ability to track the entire learner and account journey throughout our training, and streamlined our operations to better pursue opportunities for growth in the future.

Merav Yuravlivker

CEO

Data Society

How Administrate Makes Data-driven Decisions a Repeatable, Scalable Practice

Administrate leverages course data, learner data, training demand, and operational requirements or constraints to solve complex decisions. Here are some of the features that our clients use turn training data into organizational intelligence.

  • Scheduler: A suite of features that work together to plan, solve, and schedule training events for an entire quarter (or longer) with a few clicks.
  • Training Demand Forecasts: See at a glance predicted training demand over time, including specific information on resource demand.
  • Intelligent Booking: Instructors and other resources are booked intelligently so there are no more empty seats at your events, or double booked resources.
  • Automated Data Entry: Capture relative training data from anywhere in Administrate, or other business systems, and automatically apply it to the correct templates.
  • Rapid Reporting: Create customized reports faster, complete audits ahead of schedule, and answer utilization, need, and forecast requests with data-confirmed decisions. Administrate doesn’t produce pre-made reports, but pulls real-time data with your specific requirements to tell your story.

By combining data literacy, dispelling president training data myths, and leveraging a training operations platform like Administrate, you can turn decision-making into an economy of scale.

Fuel Strategic Decisions

Powerful training management starts with Administrate.