How Using Real Data for Testing and Training Can Improve Your Change Management Strategy

Discover how using real data during testing and training is a secret weapon for your change management strategy.

Carrie Gabris

BC Practice Director

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    If you want employees to drive outcomes, you have to show them exactly how to make that happen – using real-world insights to embed change into daily operations and prevent employees from backsliding into old habits.

    When training is limited to hypothetical scenarios, employees miss critical opportunities to solve problems and drive meaningful improvements.

    That means, employers wait longer to reap the benefits of their tech investments, as end-users struggle to translate what they’ve “learned” into real-world applications.

    In this article, we’ll explain why using real data during testing and training is change management’s secret weapon.

    Business Leaders Guide to the New Digital AgeBusiness Leaders Guide to the New Digital Age

    Reinforce Adoption & Set the Stage for Success

    Incorporating real data into testing and training is key when it comes to driving adoption and long-term success.

    Low adoption rates can lead to all sorts of problems. We’re talking: data silos, delays, bad data, privacy violations, and so on – all of which, introduce major risks to your business.

    Again, one of the biggest problems with corporate training programs is that content and lessons focus exclusively on hypothetical scenarios that have nothing to do with end-user goals.

    What happens is, users power through the training without any problems. But – when it’s time to put those new skills to use, they get stuck because they don’t know how to use the new tools in context with their role, priorities, or even the same general use case. And, unsurprisingly, users give up on the change.

    Data allows you to put that change in context with end-user roles and create resources and safeguards that minimize friction and help people succeed.

    Say you’re teaching your marketing team how to interpret insights and use them to inform their content strategy. In that case, running them through a generic training won’t provide much value beyond showing them how to get around their new workspace.

    Incorporating real data about customers, trends, behaviors, etc. into training sessions, allows marketers to learn new skills in context with their role. They can practice pulling reports and using insights to develop relevant content, run multivariate tests on messaging, or refine their campaign strategy.

    You might also use process and usage data to promote and automate best practices. This allows you to create built-in guardrails that prevent employees from making costly mistakes that could undermine your business.

    For example, Microsoft customer Dematic builds custom solutions that help clients optimize their own supply chain operations.

    Because the company works with a lot of sensitive data, they must be absolutely certain every custom solution meets customer and compliance requirements – and includes baked-in threat protection.

    Azure’s infrastructure as code services allowed the Dematic team to build a flexible, standardized security solution they could easily scale – and adapt to fit each client’s unique needs.

    As a result, Dematic was able to establish and enforce security policies and automatically generate compliance reports, as well as establish 99.99% uptime – which enabled them to consistently meet service level agreements with customers.

    Find and Fix Problems Before the Go-Live

    Relying on hypothetical scenarios and sample data also makes it difficult, if not impossible, to identify and eliminate problems before they fall through the cracks.

    Using actual data during the testing process is crucial when it comes to creating a secure environment. For example, you might use data to proactively address vulnerabilities — misconfigurations, missing patches, etc. or analyze real-time risk analytics to learn more about device health and user behavior.

    That data can then be used to automate best practices and governance, correlate security signals across multiple pillars, and detect and respond to threats.

    You might also set up a sandbox replica of your production environment to test security patches and identify risks early on. Or, you can even run attack simulations to help your team prepare for future ransomware attacks.

    It’s also an opportunity to learn how new systems and processes perform under a variety of conditions so that you can ensure that your team is ready for whatever comes next.

    Identify the Most Effective Ways of Working

    Using real data during training and testing scenarios also allows you to identify the most effective processes and workflows.

    If you’re using Dynamics 365, you might train teams to leverage capabilities like process mining or robotic process automation.

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    When given real data, these tools can surface opportunities for improvement and AI recommended next steps. That, in turn, allows you to optimize processes before the go-live. The Power Automate Process Advisor tool is super useful here. It uses business data and recordings to discover optimization opportunities.

    HR teams might use workforce analytics (which focus on recruiting, hiring, and retention) to quantify the impact of specific initiatives and measure progress against high-level goals.

    When combined with employee survey data, satisfaction scores, and critical KPIs, HR can look at their talent management strategy and find out where they’re falling short. Then, from there, make changes to that strategy before the official rollout.

    Use Data to Drive Innovation

    According to Google, organizations that embrace a “test-and-learn mindset” see 3x greater returns from digital investments compared to their less mature counterparts.

    These companies take an always-on approach to testing, allowing them to build a culture that supports experimentation and agility.

    The Google piece focuses on how brands like and Deciem used data to transform their marketing strategies and messaging. But, the same logic applies to other business areas and initiatives.

    For example, WPP is the largest creative transformation company in the world – boasting a 100k-employee workforce that spans 80+ countries. The firm helps clients connect with the public in creative new ways – and began investing in AI technology as a means of building on existing capabilities.

    A big part of that effort was building a distributed innovation program, centered on the idea that the best ideas are developed as close to the client as possible.

    The firm’s agencies develop solutions for specific client needs, which are then reused across other business areas.

    Successful projects are repurposed into templates anyone can use to build their own solutions. Users can draw from a library of known solutions and apply their own ingenuity and expertise to solve problems and collaborate with clients.

    What’s really interesting though, is that WPP captures and analyzes tons of data to learn how people use templates, interact with data, and explore potential solutions.

    Those findings are then made accessible to employees and clients across all agencies – allowing them to share tips, tricks, and lessons learned from past experiences. Ultimately, the firm says its ability to collaborate and solve real-world problems with data and AI is its greatest asset.

    According to Microsoft, WPP’s success in combining human creativity with tech stems from its commitment to culture. Sure, it helps to have access to big budgets and cutting-edge technologies but it’s the people that turn those resources into real value.

    Maximize the Impact of Training & Development Programs

    Capacity for change is a competitive advantage. Business leaders must look at training and skills development investments the same way they look at acquisitions, infrastructure upgrades, or product development.

    You can use data to support talent development in a few different ways. For starters, you can capture real-time skills data to identify gaps, and from there, take proactive steps toward filling them in.

    In that instance, you might look at, say, overall sales performance – starting with metrics like close rate, pipeline velocity, or revenue generated within a certain time frame. Then, you’ll dive deeper, correlating actions with wins or losses.

    Those insights can then be used to develop more relevant and effective sales training programs, strategies, and supplemental resources.

    If we’re sticking with the sales example, that means you’ll likely use skills/performance/financial data to define training and coaching programs.

    But, beyond that, you’ll also use subsets of real customer data, competitive & market intelligence, financial data, etc. during your training sessions. That way, sellers can hone their skills based on real customer needs, economic conditions, and so on, rather than vague hypotheticals.

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    Using real data during training and testing also helps employees develop skills that boost organizational agility.

    Taking subsets of your actual business data and using predictive ML models to prepare for all plausible scenarios gives employees an opportunity to practice making predictions and correlating actions with specific outcomes.

    For example, you might incorporate predictive modeling into training and testing strategies to prepare for multiple versions of the future. This is an essential capability for improving agility, resilience, and flexibility – all key ingredients for lasting success.

    When everyone understands what to do if there’s another global pandemic, a critical supply chain disruption, a major flood, or, there’s an unexpected growth spike, your organization is in the best position to take action. In turn, that means you’re able to make the most of new opportunities or mitigate the damage of an unexpected disaster.

    Final Thoughts

    The big takeaway here is, training and testing should always be informed by real data.

    From a training perspective, this approach not only helps employees (at all levels) understand what actions they should take under what circumstances. It also goes a long way in cultivating the mindset, data-savvy, and future-ready skills that orgs need to build “resilience,” “agility,” and whatever other buzzwords are synonymous with “survival.”

    Velosio’s Microsoft experts help organizations transform the way they data, automate workflows, and deliver valuable services to their clients. Get in touch to find out how.

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    Carrie Gabris

    BC Practice Director

    Follow Me: