Humanity is expected to consume around 185 Zettabytes of data by this year. Think about that: it would take you, by yourself, over 5.5 billion years of continuous, unbroken streaming to consume that much data. And here we are in 2025, less than 50 years after the official ‘birthday’ of the internet (Jan 1, 1983, for trivia seekers).
While people are drowning in data, companies are struggling to extract insights from the deluge. Despite investing heavily in Business Intelligence (BI) tools, dashboards, and analytics platforms, many organizations are unable to mine the data for insights and actionable decisions that drive real impact. This gap between data visualization and execution – often called the “actionability gap” – hinders growth, efficiency, and competitive advantage.
To bridge this gap, businesses must move beyond static dashboards and adopt a decision-centric approach – one that integrates strategy, data, technology and advanced analytics to drive measurable outcomes.
Dashboards Cannot Solve Data Overload
One way to solve the data deluge is to build dashboards that capture the data and tailor them to the metrics that the business needs. Modern BI tools like Power BI, Tableau, and Looker create the dashboards and provide rich visualizations, but they often fall short in driving real business decisions. Why?
- Data Silos: Data environments do have humongous amounts of data available across multiple granularities. But this ‘gold mine of data’ on which companies operate, are nothing but heaps of under-utilized data typically working as ‘data repositories’ belonging to or controlled by a Business Unit which are not easily or fully accessible by others within the organization. Eg: Marketing and Sales have separate databases and can’t easily access or use each other’s data.
- Lack of Centralized Data Strategies: Poor planning during digital transformations, no right data governance in place are equally responsible for unactionable dashboards available in bulk.
- Data Overload: Teams drown in metrics without clear prioritization. Many a time, the metrics might be vanity metrics as against the ones that provide real insight. Businesses have to be watchful, as these metrics might present a picture that may have little relationship with either the strategic or the tactical business goals.
- Lack of Context: Dashboards show “what” happened but not “why” or “what to do next.” Dashboards provide historical data, and any insight that is drawn from them has to be seen in the light of the present-day dynamics. Data analysis is, at its heart, an attempt to find a pattern within, or correlation between, different data points. From these patterns and correlations, insights, inferences, and conclusions can be drawn.
- Siloed Insights: Data remains disconnected from business processes. For example, Accounts Receivable (AR) data by itself is of limited value unless the same is shared with the sales teams and they take action.
From Insights to Action: A Framework for Decision-Centric Analytics
To transform data into decisions, businesses must adopt a structured approach, often supported by business transformation consulting services. Here’s how:
- ‘Enrich’ & Get ‘Data-Rich’
The goal of data enrichment is to make data more complete, accurate, and valuable for decision-making, personalization, analytics, or automation. Industries, more often than not, miss out on this easy yet most effective stage in their Dashboard journey – ‘Derive’ Variables to ‘Drive’ Decisions. Adding contextual data around Demographics, Firmographics, Behaviors, Geographics, Psychographics etc can enrich the data right under your nose. - More Dashboards ≠ Better Insights
Focus on dashboard adoption, clarity, and business impact, not sheer volume is a key consideration. Instead of asking: “How many dashboards do we have?” we need to ask: “Which dashboards are critical for decision-making?” or “Are our dashboards trusted, accurate, and actionable?” - Align Data with Strategic Business Goals
Instead of tracking vanity metrics, focus on KPIs tied to business outcomes (e.g., revenue growth, cost reduction, customer retention). When Practus led a full-scale business transformation for a leading global stonecraft manufacturing business, one of the key challenges was the lack of performance measurement against strategic goals: there was no real visibility into the company’s performance because they weren’t tracking the right metrics. We implemented a Balance Scorecard for the company, defining goals and creating a set of over 75 KPIs that would help them track and measure their progress vis-a-vis the pre-defined goals. - Embed Analytics into Workflows
Integrate BI tools with operational systems (e.g., CRM, ERP) to trigger automated actions. Keeping the analytics in a silo for analysis and insights from a separate tteam will be less useful than enabling the actual users of the data to consume them and take action on the same. A sales dashboard that automatically flags high-risk deals and suggests next steps will be a very useful tool in the hands of the sales team, as it can lead to real-time action, as against taking action after a time lapse.
- Foster a Data-Driven Decision Culture
The journey to becoming more data-driven begins with a conscious commitment to think analytically, not just in professional settings, but also in everyday life. While it sounds straightforward, developing an analytical mindset requires ongoing effort and intentional practice.
Start by observing the data in your daily environment—whether reviewing reports at work, noticing purchasing habits while shopping, or analyzing commuter trends on your way home. Identify patterns in these scenarios and consider what insights they might reveal. Ask yourself why those patterns occur and what they might indicate.
This habit of continuously seeking meaning from data helps sharpen your analytical thinking. Over time, it enhances your ability to make informed, evidence-based decisions—both in business and in life. Becoming truly data-driven is less about tools and more about cultivating this mindset.
- Leverage AI & Predictive Analytics
Move from descriptive (“what happened?”) to prescriptive (“what should we do?”) analytics.
Predictive analytics leverages historical data to forecast future outcomes, enabling smarter, data-driven decision-making. It is widely applied across industries, from predicting financial performance to anticipating equipment failures or customer behavior. In healthcare, predictive algorithms can detect early signs of allergic reactions and initiate life-saving interventions. By closing the gap between insight and action, predictive analytics empowers organizations to respond proactively rather than reactively. Whether you’re planning strategy, reducing operational risks, or enhancing customer engagement, predictive analytics provides the foundation to transform data into foresight and competitive advantage.
In the manufacturing field, algorithms can be trained using historical data to accurately predict when a piece of machinery will likely malfunction. When the criteria for an upcoming malfunction are met, the algorithm is triggered to alert an employee who can stop the machine and potentially save the company thousands, if not millions, of dollars in damaged product and repair costs. This analysis predicts malfunction scenarios in the moment rather than months or years in advance.
Key Takeaways for Closing the Actionability Gap
Going beyond gut-brain to data-driven decision-making as a process requires more than tools. It calls for a mindset change, process overhaul, and upskilling across the board. Dashboards are just a starting point. Real competitive advantage and true impact come from closing the actionability gap – turning insights into implementation.
At Practus, we help CXOs define and implement a culture of data-driven decision-making. By defining clear KPIs and implementing real-time performance tracking with AI-powered insights, our business consulting services enable leaders to separate strategic insights from day-to-day operational data, bringing clarity and focus to decision-making across:
- People
We train teams to move from passive reporting to active decision-making, using real-time data relevant to their functions. - Processes
We break down data silos and embed insights into daily workflows—so data becomes a driver, not an afterthought. - Technology
We assess your current data landscape, identify capability gaps, and implement solutions that enable reliable analytics.
The real value of data lies in how it’s used. At Practus, we help organizations turn data into action, building a culture where informed decisions drive measurable outcomes. For businesses looking to lead, that culture isn’t just helpful – it’s critical.
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By Priyanka Baram
