Data Adoption, Done Right: Tips That Stick
You’ve invested in a great data solution. In the first few months, everything works perfectly, and the team is excited. But after a while, cracks start to appear: reports load slowly, refreshes fail, or reports aren’t used at all. Sound familiar?
Successful data adoption is more than just getting started. It’s about sustained use and stable performance.
About this webinar
In this short but powerful webinar, we’ll show you how to successfully embed data solutions in your organization—and how to prevent them from losing effectiveness over time. You’ll get practical, actionable tips from real cases and learn how our support team can help ensure continuity.
We’ll cover:
- What data adoption really means (and why it often fails)
- Practical tips that actually work in the field
- How to keep your solutions healthy: common issues and how to avoid them
- When it makes sense to engage our support team
What’s in it for you
In just 20 minutes, you’ll learn:
- How to accelerate adoption within your team
- How to prevent technical issues before they impact you
- How to keep dashboards and reports consistently valuable
Want your data solutions not just to launch, but keep running smoothly? Watch this webinar now and discover how we can help.
Rewatch this webinar?
Watch the webinar recording and apply the lessons to your current roadmap
Solid talk: From ‘having data’ to ‘using data’ with Schiphol’s Chief of Data
Jonathan Aardema (Co-Founder, Rockfeather) sits down with Maarten van den Outenaar, Chief of Data at Schiphol, for a straight-talk session on data strategy with impact. They talk about field-tested practices, honest pitfalls, and concrete examples you can lift into your own roadmap the same week.
Why many data strategies stall
Big ambitions die in execution when teams ship impressive prototypes that users don’t adopt, or when priorities drift away from business goals. Maarten shares the tell-tale signals:
- Teams can’t name the user, the decision, or the measurable outcome.
- Success looks like “we built it,” not “it’s used and it improved X.”
- Initiatives run in silos, costs climb, benefits aren’t captured.
Bottom line: strategy only matters if it’s executed—and used.
What actually works in practice
From rail and construction to aviation, the patterns repeat. The wins come when you:
- Anchor to business outcomes – tie every data product to a concrete operational or commercial goal.
- Design for adoption, not just accuracy – remove friction in the real context of work (sometimes that means paper, not a tablet on a vibrating machine).
- Keep the human in the loop – automate the boring, elevate expert judgment where it adds value.
- Focus on rate of adoption, not rate of change – pace your roadmap to what the organization can truly absorb.
Example discussed: repurposing advanced computer vision from a long-horizon R&D track into a maintenance use case that delivered immediate, visible value for front-line teams.
How to align teams and reduce waste
Great data teams can build almost anything; great strategies help them build the right things:
- Translate corporate strategy into a clear portfolio of data products.
- Set explicit user, decision, and metric for each product.
- Cut duplication across teams; standardize where it saves time; differentiate where it drives impact.
Keeping it alive after the first quarter
Momentum fades unless you make progress visible and leaders accountable:
- Publish a simple “highlight report” every half-year mapping business objectives → data products → realized outcomes.
- Practice radical transparency with sponsors – what’s used, what’s not, and what stops.
- Codify ownership in the business – adoption, feedback, and action live there, not just in the data team.
When you should watch this
If you lead data, analytics, or IT and want your investments to show up in operational KPIs—not only in demos—this conversation gives you the playbook and the pitfalls to avoid.
What you’ll take away in 20 minutes
- How to link data products to real business goals and user decisions.
- How to diagnose adoption gaps fast—and fix them.
- How to pace your roadmap to organizational absorption.
- How to make value visible so sponsorship and momentum stick.
Rewatch this webinar?
Watch the webinar recording and apply the lessons to your current roadmap
Every dashboard should answer four questions
How do you create reports that don’t just show numbers but directly guide decisions? In this webinar with Zebra BI, we shared the four questions every dashboard should answer.
Rockfeather and Zebra BI tackled the biggest challenges in dashboarding: too many KPIs, lack of context, and reports that look polished but fail to support decision-making.
At the heart: every dashboard should answer four questions:
- Is performance good or bad?\
- How good or how bad?
- Why is it so?
- What are we going to do about it?
This framework ensures dashboards don’t become cluttered with KPIs and visuals that confuse instead of clarify.
Key takeaways from the webinar
- Always add context: benchmark against plan, forecast, or last year.
- Standardize: the same visual should always convey the same message.
- Simplicity over decoration: highlight only what matters.
- Build hierarchy: top KPIs first, with drill-downs for detail.
- Connect data to action: make it clear what decisions follow from the numbers.
Real-world examples
Heijmans standardized reporting across units, leading to faster, more consistent decision-making. KPN created a self-service dashboard aligned with IBCS standards, giving users ownership of insights and reducing BI workload.
Your next step
Want dashboards that truly make a difference? Start by applying the four-question test to your reports, or let Rockfeather help you build dashboards that support faster, smarter decisions.
Rewatch this webinar
Missed the webinar, or want to rewatch the examples? Here you go!
Why most dashboards fail and how you can fix it
Your organization creates many reports, dashboards, and quick analyses. But why do they all look different? Why is there no clear and standard way of reporting? Many industries use standard communication. So why not do the same for your business reports? If reports are inconsistent, it is harder to understand data, make good decisions, and take action.
What Will You Learn in This Webinar?
- Why many dashboards fail – and how to fix them.
- How IBCS helps you create clear and standardized reports.
- Which companies successfully use IBCS and how it improves their decision-making.
Bring Clarity and Structure to Your Reports with IBCS
The International Business Communication Standards (IBCS) help you create clear and standard reports. This makes it easier to understand insights and make better decisions.
A study from Technische Universität München (TUM) shows that using IBCS correctly can reduce analysis time by 46% and improve decision-making by 61%.
Curious to see how this works? We explain everything in just 25 minutes.
Watch this webinar
Work smarter without new tools: Power Platform in action
In this online masterclass, we’ll show you how to streamline existing processes and make them future-proof. No complex IT projects—just practical solutions within your current Microsoft environment.
Many decision-makers are unaware of the full potential of Microsoft Power Platform, and that’s a missed opportunity. This platform offers countless practical applications to optimize and digitize business processes.
The good news? Chances are, you already have it!
But are you using Power Platform to its full potential? Without a structured approach, its components are often used in isolation, limiting their impact. Curious about how your organization can unlock more value from technology you already own? In this masterclass, we’ll show you how.
Power Platform in Action: 3 Use Cases, 1 Masterclass
In this session, we’ll take you behind the scenes and show you exactly how different Power Platform applications work together to streamline business processes. No theory—just a deep dive into three powerful implementations:
- Order2Cash – From invoice to payment without the hassle. Automate invoicing, payment reminders, and cash flow analysis with Power Automate, Power BI, and Power Apps. Fewer errors, faster payments.
- OnboardingApp – Give new employees a smooth start. Automate system access, equipment requests, and training with smart workflows and data-driven insights.
- Customer Order Portal – Fewer emails, more control. Let customers check their orders and statuses themselves, fully integrated with your backend systems. More efficiency for them, less manual work for you.
You’ll also discover how Copilot enhances automation with AI-driven intelligence. Copilot helps you leverage data more effectively, speed up processes, and improve workflows proactively—without adding complexity.
What’s next after this webinar?
That depends on where your organization stands today. Here are three common paths we see with our clients:
1. Do nothing – and keep struggling with emails and Excel.
Sounds a bit harsh, but it’s what many teams end up doing (often unintentionally). Everything stays the same: manual processes, error-prone tasks, and lost time.
2. Start a small-scale pilot on your own.
You’ve got the ideas—now it’s time to act. Start with one painful process—think onboarding, order handling, or reporting. Build your own solution with Power Automate or Power Apps and learn as you go.
👉 Tip: look for someone on your team who already knows their way around Power BI or SharePoint—they’re often up and running faster than expected.
3. Map your opportunities together with us.
We’d love to help you figure out:
📌 Where the biggest wins are
⚙️ Which processes can be smartly automated using what you already have
💡 How to make sure users actually start using it
👉 Plan a no-strings-attached session – and let’s explore what works best for your situation.
You're in!
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Enjoy this webinar
AI Agents: Your New Colleague in Data Analysis
Making data-driven decisions doesn’t have to be complicated. With AI agents, you no longer need endless dashboards or manual reporting. These digital colleagues deliver insights within seconds, spot trends, and even build your presentation. In this article, you’ll discover how AI agents like Zebra BI and Microsoft Fabric Data Agent are already transforming the way organizations work with data.
We’ve all been there. You open an Excel file, see a mountain of sales data, and wonder: Where do I start? Now imagine skipping the filtering, clicking, and chart building. Imagine pressing a button and instantly getting a clear overview, complete with insights and ready-made slides for your next meeting. Good news: that’s not the future, it’s already possible. Thanks to AI agents.
Stop drowning in data, start using it
The concept of data-driven work has been around for years, but reality often lags behind. According to 360Suite, only 26% of employees effectively use their BI tools. Not because they don’t want to, but because it remains complex. Reports take time to create. Extracting insights requires expertise. And as a result, decisions get delayed.
That’s exactly where an AI agent helps. It makes data accessible, understandable, and immediately actionable—in seconds.
What exactly is an AI Agent?
It’s not a robot. It’s not a chatbot. It’s simply a smart digital colleague that helps you make sense of your data. Zebra BI is a perfect example. You upload your dataset, and within moments, you get a visual overview with clear conclusions. The tool identifies trends, suggests next steps, and even helps build your presentation.
Microsoft Fabric Data Agent takes it even further. It monitors your data in real-time. Think of it as a colleague who immediately alerts you when something unusual happens, like a sudden drop in revenue. It provides context and recommendations, so you no longer depend on monthly reports. You can take action right away.
The best part? You interact with these tools as you would with a colleague. Just type, “Why has the margin dropped in the South region?” and you get a clear, straightforward answer.
What does this mean for data professionals?
AI doesn’t replace your work, it makes it better. You spend less time building dashboards and more time where it matters: helping colleagues make smart decisions. Your role shifts from builder to advisor, from creator to coach.
You ensure the data is accurate. You help shape the right questions. And you make the difference between simply reporting and actually improving.
What does this mean for your organization?
AI agents have a real impact. They reduce the pressure on scarce specialists. They speed up decision-making. And most importantly, they help your organization become more agile. When data reaches the right people faster, they can act faster. It’s that simple.
According to Accenture, employees lose an average of five workdays per year due to poor data literacy. That’s a full workweek per person, time and money wasted.
Meanwhile, G2 reports that the use of BI solutions has increased by 49% since the pandemic. The need is clear. The tools exist. The only thing left is to use them wisely.
The future is already here
AI agents are reshaping how we work. They make data accessible. They help you make faster decisions. And they lead to better conversations, better choices, and better results. You don’t have to wait until you’re “ready.” You can start today.
Want to see how close this future really is? Watch the video below, where the CEO of Zebra BI demonstrates how it works; live, simple, and no gimmicks.
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Video: AI Agents with Zebra BI
By Andrej Lapajne, Founder & CEO of Zebra BI, during our Data & Automation Pitstop 2025.
How Schiphol puts data at the heart of every key-decision
Schiphol Group is transforming how decisions are made; by putting data at the centre of daily operations. In this article, Maarten van den Outenaar explains how the airport empowers employees, aligns data with strategy, and navigates technology adoption at the right pace.
How can organizations ensure every critical decision is genuinely supported by data? Maarten van den Outenaar, Chief Data Officer at Schiphol Group, emphasizes a strategic vision built around empowering employees to integrate data into their daily decisions. Schiphol’s vision “Data at the heart of every key decision”, reflects a broader organizational transformation towards data-driven decision-making.
Why data-driven decisions matter
Organizations continuously face the challenge of timing their technology adoption effectively. As history shows through various industrial revolutions, adopting technology too early or too late both carry risks. Schiphol recognized that integrating data effectively into the organization’s decision-making processes required a balanced and strategic approach.
Van den Outenaar highlights three primary ways data can improve organizational outcomes:
- Efficiency: Streamlining existing processes.
- Effectiveness: Enhancing decision quality and outcomes.
- Diversification: Applying successful practices across various organizational domains.
Schiphol’s strategic vision: Autonomous Airside
Schiphol Group’s strategic goal, encapsulated as “Connecting your world with the most sustainable and high-quality airport,” focuses on quality network connections, customer service excellence, employee satisfaction, community engagement, and sustainability.
Central to this vision is the concept of an autonomous airside: a fully electrified airport area leveraging data and IT to minimize environmental impact and optimize operational efficiency. However, reaching full decision automation remains cautious, with human judgment playing a vital role even at advanced stages.
Aligning data strategy with organizational decisions
To achieve meaningful integration of data into everyday decisions, Schiphol approached departmental leaders, asking them to identify their top three decisions. This approach ensured:
- Clear prioritization of data initiatives.
- Strong alignment with strategic objectives.
- Practical focus on measurable outcomes.
By clearly defining and supporting key decisions, Schiphol ensures that data initiatives genuinely impact strategic objectives.
Empowering employees through data
Effective data strategies require putting employees at the center. Employees are empowered through education, support, and the integration of digital expertise from Schiphol’s Center of Excellence. Van den Outenaar emphasizes a collaborative approach, combining technical knowledge with domain expertise to effectively bridge the gap between rapid technological developments and employee adoption rates.
Navigating technology adoption
Organizations face continuous pressure from rapidly advancing technologies, often outpacing organizational readiness. Schiphol tackles this issue using the S-curve model—common in investment circles—to carefully time technology adoption. The S-curve approach:
- Guides incremental maturity growth in data capabilities.
- Enables timely assessments and adjustments.
- Facilitates agile, strategic progression towards data maturity.
This incremental and evaluative approach ensures organizations adapt at a sustainable pace, avoiding technology fatigue and resource misallocation.
Matching employee needs with technological capabilities
Successful implementation of data initiatives relies on identifying and prioritizing employee tasks that most benefit from technological assistance. Schiphol pairs employee needs with technological potential, creating actionable matrices that highlight optimal implementation opportunities.
Key considerations include:
- Identifying tasks suitable for automation or enhancement.
- Recognizing employee openness to technology.
- Prioritizing initiatives with significant impact potential and high employee enthusiasm.
Practical Impact and Real-world Application
Van den Outenaar underscores the importance of tangible improvements. By clearly demonstrating how data initiatives enhance employee performance and organizational outcomes, Schiphol achieves broader organizational buy-in. Specific reports and dashboards illustrate the practical benefits directly linked to employee needs, reinforcing strategic alignment.
Continuous Improvement through strategic alignment
Schiphol’s approach to data strategy highlights the importance of continuous improvement through strategic alignment, employee empowerment, and agile technology adoption. By placing data at the heart of key decisions and strategically aligning technological maturity with organizational readiness, Schiphol demonstrates a robust blueprint for successful data integration.
Artificial Intelligence is ready!
In this interview, Jonathan Aardema talks with Prof. Eric Postma (professor of Cognitive Science and Artificial Intelligence at the University of Tilburg) about the why, how, and what of artificial intelligence applications. What do we see in practice, and what does science say about it?
Visiting London for the Tableau Partner Executive Kick-Off 2020
Every year Tableau invites its most valuable partners to kick off the new year together. The theme for this year was Accelerate, so let’s get right to the point. This exciting event was focused on three main areas.
Mastering DAX
Keeping your skills up to date is crucial when you work with the newest technology. At Rockfeather, we challenge each other to be the best version of yourself. That’s why I attended the mastering DAX course. DAX (Data Analysis Expressions) is a formula expression language. Next to Power BI, DAX is applied in Excel Power Pivot and tabular models in SQL Server. Learn it once, use it tomorrow.
How do you choose the right KPIs, without losing sight of your strategic goals?
Selecting effective Key Performance Indicators (KPIs) is often more complicated than it appears. Organizations frequently find themselves measuring numerous KPIs without achieving clarity on performance or strategy alignment.
Prefer watching to reading? Check out the video at the top of this page to hear Bernie Smith explain it himself.
Bernie Smith, a recognized expert in KPI development, emphasizes this challenge through a compelling analogy: poorly coordinated decisions, much like a street renovation immediately followed by tree removal, lead to meaningless outcomes despite good intentions and substantial investments.
The Persistent Challenge: Aligning KPIs with Strategy
Smith notes a recurring issue in organizations, the disconnection between chosen KPIs and strategic objectives. Many KPIs, although individually logical, fail collectively because they are not aligned or prioritized correctly. This misalignment results in wasted effort, resources, and ultimately confusion rather than clarity.
To address this challenge, Smith developed the Results Orientated KPI System (ROKS), known informally as the ROKS method, a structured seven-step process focused on aligning KPIs directly with strategic outcomes.
Introducing the KPI Tree Concept
Central to the ROKS method is the idea of KPI Trees, an evolution of the traditional strategy mapping approach popularized by Kaplan. KPI Trees visually break down broad strategic objectives into specific, measurable elements, enabling better alignment and clarity.
Smith illustrates the KPI Tree method with a simple personal example: aiming for good health. The top-level strategic objective—being healthy—is broadly accepted but not directly measurable. Breaking it down, Smith identifies measurable components such as exercise frequency, sleep quality, and dietary habits. Each subsequent level adds specificity, eventually reaching clearly measurable KPIs, like daily calorie intake.
Benefits of KPI Trees:
- Clarity and Simplicity: Complex strategies become clear and actionable.
- Alignment and Engagement: Collaborative construction of KPI Trees fosters consensus and team buy-in.
- Visualizing Conflicts: Clearly illustrates potential conflicts between KPIs, ensuring balanced decision-making.
Dealing with KPI Overload: The Importance of Shortlisting
Despite their advantages, KPI Trees can lead to an overwhelming number of potential KPIs. Smith identifies two typical mindsets regarding KPIs:
- Dreamers: Those inclined to measure everything imaginable.
- Pragmatists: Those cautious about adding KPIs, mindful of measurement complexity and workload.
To manage this tension, the ROKS method employs a rigorous shortlisting process, prioritizing KPIs based on their strategic importance and ease of measurement. This critical step ensures that only relevant, manageable, and impactful KPIs remain.
Practical Scalability and Adaptability
A significant advantage of KPI Trees and the ROKS method is their scalability. They are designed for adaptability across different organizational contexts—from banks and universities to manufacturing firms. Smith highlights that, although KPI Trees can initially appear complex, they become practical and reusable tools, easily adjusted to fit unique organizational processes.
Strategic Alignment as the Ultimate Goal
Ultimately, effective KPI selection is less about having many KPIs and more about choosing the right ones. Smith’s ROKS method and KPI Trees help ensure every KPI directly supports strategic objectives, clearly linking performance measurement with organizational goals.
In conclusion, organizations need a systematic approach like the ROKS method to avoid common pitfalls in KPI selection. Aligning KPIs clearly with strategic objectives ensures clarity, relevance, and actionable insights; critical components for sustainable organizational success.
Artificial Intelligence is ready!
In this interview, Jonathan Aardema talks with Prof. Eric Postma (professor of Cognitive Science and Artificial Intelligence at the University of Tilburg) about the why, how, and what of artificial intelligence applications. What do we see in practice, and what does science say about it?
Visiting London for the Tableau Partner Executive Kick-Off 2020
Every year Tableau invites its most valuable partners to kick off the new year together. The theme for this year was Accelerate, so let’s get right to the point. This exciting event was focused on three main areas.
Mastering DAX
Keeping your skills up to date is crucial when you work with the newest technology. At Rockfeather, we challenge each other to be the best version of yourself. That’s why I attended the mastering DAX course. DAX (Data Analysis Expressions) is a formula expression language. Next to Power BI, DAX is applied in Excel Power Pivot and tabular models in SQL Server. Learn it once, use it tomorrow.
Is AI-driven decision making the answer to the low adoption of Business Intelligence?
Business intelligence (BI) has long promised organizations the ability to make smarter, data-driven decisions. Yet, despite significant investments, BI adoption remains low, with only 26% of enterprises fully utilizing their analytics tools. Executives remain skeptical, with just 32% confident in their ability to make meaningful data-driven decisions, while a lack of adequate data skills has resulted in inaccurate decisions for 41% of executives.
The question, therefore, arises: can AI-powered analytics provide the breakthrough organizations need?
The Limits of Traditional BI
The persistently low adoption rates of traditional BI tools stem from several fundamental challenges:
- Complex and unintuitive user experiences discourage widespread usage.
- Employees frequently feel overwhelmed by the complexity of data analytics.
- Specialized knowledge and training are necessary to leverage traditional BI effectively, creating bottlenecks.
These barriers result in missed opportunities and potentially costly business mistakes.
AI: Bridging the Gap in Data Adoption
Tools incorporating artificial intelligence, like Zebra BI, offer a new approach by directly addressing these barriers:
- Automation of Analytical Processes: AI-driven tools can instantly generate insights from raw data, significantly reducing manual effort and time spent on data preparation.
- Intuitive Interaction: AI enables users to engage naturally with data, posing questions in conversational language and receiving immediate, actionable insights.
- Democratization of Data: By eliminating the need for specialized technical knowledge such as complex scripting languages (e.g., M and DAX), AI makes sophisticated data analytics accessible to a broader range of business users.
Data Quality Remains Paramount
Despite the impressive capabilities of AI, quality data remains the critical foundation for any meaningful analytics initiative. AI emphasizes and reinforces the necessity of maintaining accurate, well-organized data sets. Without high-quality input, AI outputs remain unreliable.
Key Benefits of AI-Enhanced Analytics
The incorporation of AI into data analytics offers several notable advantages:
- Rapid Processing Power: Quickly analyzing vast datasets to identify key trends.
- Enhanced Pattern Recognition: Automatically detecting and explaining data anomalies and trends.
- Cost Efficiency: Significantly reducing dependence on costly external consultants and specialized infrastructure.
- Interactive Collaboration: Facilitating dynamic interactions between users and AI agents to produce insightful and collaborative analyses.
- Greater Accessibility: Empowering all users, regardless of technical skill level, to meaningfully engage with data.
Making Analytics Actionable
Beyond producing insights, the real value of analytics lies in the ability to make informed, actionable decisions swiftly. AI-driven analytics tools streamline the process from data collection to actionable insights, dramatically shortening the decision-making cycle. This transforms not only individual decisions but potentially reshapes entire organizational approaches to analytics.
The Future of Business Intelligence
AI-driven analytics represents a significant evolution in business intelligence, offering organizations an opportunity to overcome persistent barriers to data adoption. Companies embracing AI tools like Zebra BI position themselves strategically to achieve higher levels of analytical maturity, though the journey invariably begins with robust, high-quality data.
As we move forward, the question is no longer whether organizations should consider AI-driven analytics, but how quickly they can adapt their processes and culture to harness its potential fully.
If you are interested in exploring the practical aspects of AI-driven analytics, the presentation at the top of this page by Andrej Lapajne offers deeper insights and valuable perspectives.
Sources: 360Suite’s Business Intelligence Survey (2020), Accenture (2020), G2 (2023), Forrester (2022), Datacamp (2023)
Artificial Intelligence is ready!
In this interview, Jonathan Aardema talks with Prof. Eric Postma (professor of Cognitive Science and Artificial Intelligence at the University of Tilburg) about the why, how, and what of artificial intelligence applications. What do we see in practice, and what does science say about it?
Visiting London for the Tableau Partner Executive Kick-Off 2020
Every year Tableau invites its most valuable partners to kick off the new year together. The theme for this year was Accelerate, so let’s get right to the point. This exciting event was focused on three main areas.
Mastering DAX
Keeping your skills up to date is crucial when you work with the newest technology. At Rockfeather, we challenge each other to be the best version of yourself. That’s why I attended the mastering DAX course. DAX (Data Analysis Expressions) is a formula expression language. Next to Power BI, DAX is applied in Excel Power Pivot and tabular models in SQL Server. Learn it once, use it tomorrow.