Key Takeaways

70-80% of enterprisedata remains underutilized, representing massive wasted investment in storage,processing, and licensing costs.

datasensAI’s AI-driven scoringalgorithm transforms abstract data utilization into actionable metrics,enabling data-driven resource allocation decisions.‍

ROI visibility through cost allocationanalysis empowers mid-size enterprises to reallocate licenses, eliminate waste,and justify strategic expansions.

Four-step implementation frameworkdelivers actionable insights in days with only 2-4 hours of initial assessmenttime.

The numbers tell a sobering story:Organizations invest heavily in Splunk infrastructure, yet 70-80% of theirdata remains untapped—dormant, underutilized, and generating zero businessvalue. For mid-size enterprises navigating cloud migrations, security threats, andoperational complexity, this isn’t just wasted potential—it’s wasted capital,missed insights, and competitive disadvantage.

According to Gartner, organizations wastean average of $12.9 million annually on unused or underutilized software [1],with data analytics platforms representing asignificant portion of this waste. Meanwhile, IDC research reveals thatcompanies utilize only 32% of the data available to them, leaving themajority of their information assets dormant despite substantial investment incollection and storage infrastructure.

The culprit? A decision gap that plaguesmodern data operations. Teams know they have data. They know it’s valuable. Butthey lack the visibility, actionable intelligence, and automated workflows totransform raw observability into strategic outcomes. Traditional Splunkdeployments excel at data ingestion but falter at data activation, leavingorganizations paying premium licensing fees while their most valuable insightsremain buried in unused indexes and forgotten dashboards.

This is where datasensAI, a Splunk-certified appdeveloped by bitsIO—a trusted global Splunk partner—fundamentallychanges the equation. By providing data scoring, ROI analysis, and AI-drivenuse case recommendations, datasensAI doesn't just optimize your existinginvestment; it unlocks an entirely new dimension of value that mostorganizations never knew existed.

Before exploring solutions, let’sacknowledge the uncomfortable reality facing most Splunk administrators and data strategyleaders.

Three Critical Pain Points:

1. Wasted Investments

Your organization is paying for dataingestion, storage, and processing—but extracting minimal value. Every unuseddata source, abandoned dashboard, and dormant alert represents sunk costwithout a corresponding return. Research from NewVantage Partners indicatesthat 92% of organizations are not achieving their desired outcomes from dataand AI investments [3], primarily due to utilization challenges rather thantechnology limitations.

2. Missed Opportunities

That underutilized securitylog? It could reveal breach patterns. Those unused applicationmetrics? They might predict performance bottlenecks before customers notice.Without visibility into what’s not being used, you can’t capitalize on whatcould be. According to IBM, the average cost of a databreach reached $4.45 million in 2023 [4], with many breachesinvolving indicators that were present in logs but never analyzed due toinsufficient monitoring coverage.

3. Operational Blindness

Most teams lack clear metrics on datautilization, ROI analysis, or performance benchmarking across data sources.Without a scoring mechanism to measure “data mileage,” decision-makers operateon intuition rather than intelligence. Forrester research shows that 60-73% ofall enterprise data goes unused for analytics [5], representing a massiveopportunity cost.

The result? Organizations continue expanding their Splunk footprint—addinglicenses, scaling infrastructure, increasing costs—without ever maximizing theassets they already own.

How datasensAI Closes the Decision Gap: From Data Scoring toStrategic Action

datasensAI eliminates the guesswork byintroducing a data scoring algorithm that transforms abstract utilization intoconcrete, actionable metrics.

The Data Scoring Methodology

At its core, datasensAI assigns each datasource a utilization score based on knowledge object creation and usagepatterns:

• ‍High-Score Data Sources: Actively leveraged through dashboards, reports, alerts, data models,and ad-hoc searches‍
• Low-Score Data Sources: Ingested but underutilized—prime candidates for new use casedevelopment or license reallocation

This scoring mechanism evaluates:

• Dashboard creation and interactionfrequency
• Saved search and report generation
• Alert configuration and triggerrates
• Data model utilization foraccelerated analytics
• Ad-hoc search patterns revealingorganic exploration

Why This Matters: The score isn’t just a vanity metric—it’s a decision engine that guidesresource allocation, identifies optimization opportunities, and quantifies ROIwith unprecedented precision. Studies show that organizations with mature data governance and utilization metricsachieve 5-6% higher productivity than their peers.

AI-Driven Analysis &Reporting

Once data sources are scored,datasensAI’s AI use case recommender analyzes patterns,identifies inefficiencies, and generates comprehensive reports with actionableinsights aligned to industry frameworks like MITRE ATT&CK.

• For underutilized data sources,datasensAI doesn’t just identify the gap—it prescribes specific use casestailored to your environment:
• Security monitoring templates forcompliance (GDPR, HIPAA, PCI-DSS)‍
• Performance optimization dashboards forapplication teams
• Cost allocation models for FinOpsinitiatives
• Predictive maintenance alerts forinfrastructure reliability

This transforms data observability fromreactive monitoring to proactive intelligence, where AI continuously surfacesopportunities you didn’t know to look for. McKinsey research indicates that AI-augmented analytics can improveoperational efficiency by 20-30% when properly implemented.

Maximizing Splunk ROI: The 80%More Value Promise

Let’s translate capability into tangiblebusiness outcomes. How does datasensAI deliver 80% more value from existingSplunk investments?

ROI Visibility Through CostAllocation Analysis

datasensAI provides granular breakdownsof:

• Data storage costs per source
• Processing overhead by data type‍
• License utilization efficiency acrossteams
• Cost-per-insight ratios forknowledge objects

Armed with this intelligence,organizations can:

• Reallocate licenses fromlow-performing teams to high-value use cases
• Eliminate waste by decommissioningunused data sources or renegotiating retention policies
• Justify expansion with data-drivenbusiness cases tied to measurable outcomes

According to Nucleus Research, analytics solutions deliver an average ROIof $13.01 for every dollar spent [8], but only when properly optimized andactively utilized—highlighting the critical importance of utilizationvisibility.

Take Action: Transform Your Splunk Investment Today

The decision gap between dataavailability and data action doesn’t close itself. It requires intentionalstrategy, intelligent tooling, and expert partnership.

datasensAI by bitsIOoffers:

• Rapid 2-4 hour assessment withzero external access required
• AI-powered analysis deliveringactionable insights in days
• Automated use case implementationfor top-10 underutilized data sources
• Ongoing optimization and expertsupport from certified Splunk professionals‍
• Measurable ROI through costallocation, license optimization, and productivity gains

Whether you’re struggling withunderutilized data, facing budget pressure to justify Splunk costs, or simplywant to maximize the value of your observability investment, datasensAIprovides the clarity and automation to transform potential into performance.

Ready to unlock 80% more value from your Splunk deployment?

Booka consultation with bitsIO and discover how datasensAI can closeyour decision gap, automate your monitoring, and transform your data intostrategic advantage.

Frequently Asked Questions