Businesses investing in AI-powered analytics may be overlooking the fundamental challenge around collating the data those tools need to deliver useful answers. Connecting fragmented systems and establishing consistent metrics can help businesses turn customer data into better decision-making.
When customer and operational information is spread across customer relationship management (CRM) platforms, enterprise resource planning (ERP) systems, ticketing tools, spreadsheets and other applications, each system may hold valuable information, but the fragmentation of the data makes it difficult for teams to build a complete picture of business performance, identify emerging issues and make informed decisions.
Businesses often have plenty of information available, but extracting it from different applications and turning it into useful reports creates friction.
Patterson & Associates Consulting (PAC) works with data management platform ClicData to help its clients bring information together from disconnected business systems. Customers can automate the process and create accessible dashboards that give managers, executives and operational staff a clearer view of performance and benchmarks. The aim is to turn fragmented information into actionable data that supports faster, better-informed decisions. Amber Patterson, Chief Operating Officer (COO) and acting Chief Executive Officer (CEO), explained:
“We help our clients evaluate their data and really we try to put ourselves in their shoes and understand the challenges they have. They have all of the data, but the source of friction is that the reports have to be pulled from a CRM, an ERP, or a property or case management system.”
Those systems frequently operate independently, leaving employees responsible for bringing the information together.
ClicData sees similar issues among its customer base. “The major problems that customers approach us with… is fragmented information,” said Lota Chukwu, Sales Engineer at ClicData.
Businesses need a holistic view of their operations to make good decisions, but information is frequently distributed across CRM, project management and ticketing systems.
For Patterson, the consequences extend beyond the time spent compiling reports. Without accessible, consolidated information, teams can struggle to understand what is happening across the business.
“Because it wasn’t presented in a simplified metric of a bar chart or a graph, they couldn’t see certain trends, or where things were just falling through the cracks because there was just an information overload.”
Patterson cited the example of a housing authority that uses a management system to track maintenance requests across residential buildings.
Residents submit work orders when something needs attention in their units. While the system contained valuable operational information, bringing that data into ClicData through an automated import gave the organization a clearer way to monitor performance.
Patterson explained that the reporting helped operational and IT teams identify where attention was needed, while giving managers better visibility into how quickly requests were being handled. “They could see where there were certain needs.” The organization can now track how long work orders take to complete and whether emergency requests are receiving an appropriate response.
The customer benefit is particularly important, “so that the residents get the services that they need in a timely way and that their units are safe. So that brings great value to their organization,” Patterson added.
The example indicates how connecting operational information can improve visibility into processes that directly affect service delivery and customer experiences.
As businesses explore AI-powered analytics, fragmented information can limit what these tools can accomplish.
Organizations are increasingly interested in AI, but its usefulness can be limited “when your AI only has a narrow view of that information instead of it all being together in one spot,” Patterson said.
Chukwu sees AI helping organizations democratize access to reporting and analysis, particularly among smaller businesses working with limited budgets and headcount for technical staff.
AI can help users create dashboards and answer questions about business performance without requiring a dedicated team of engineers or analysts for every task. But the underlying information still needs to be properly organized.
“Even a non-technical person can prompt an AI to build a dashboard or prompt an AI to help with answering certain questions from the data provided the data has been well organized and well curated beforehand.”
Chukwu also highlighted the importance of establishing consistent definitions for business metrics. Different departments may have different interpretations of revenue or churn, creating inconsistencies when information is brought together. Businesses need a stronger data culture, with clearly defined priorities and agreement on which metrics matter, Chukwu said.
“You can’t manage what you can’t measure. And then also at the same time, you can’t measure everything.”
Improved reporting can support decision-making at different levels of an organization, Patterson noted.
“The executive leadership staff might have a different perspective than the operational staff.” Department managers need detailed information to keep operations running smoothly, while executives need a broader view to make strategic decisions. “They’d have that clear information so that they can make the decisions they need to to pivot or position their organizations the way they need to,” Patterson added.
Patterson also emphasized that AI should help employees work more effectively, rather than making workforce reduction the primary objective.
“Helping people to do their jobs more effectively, more efficiently, and quickly, and not spending time digging through spreadsheets through data because its presented clearly.”
For organizations unsure how to approach connected data and AI-powered analytics, Patterson recommended involving the people who will actually use the information from the beginning, and bringing in a subject matter expert who understands the systems it comes from. This can help to establish consistency before reporting processes are implemented.
“Clearly define the problems that need to be solved and the outcomes that need to be accomplished,” Chukwu advised, pointing to examples of businesses that have reduced manual reporting work by automating how information is collected and distributed.
One organization recovered approximately 24 days of productivity in a year by removing the need to manually copy and paste information or manipulate data in Excel spreadsheets.
As Patterson’s examples demonstrate, the value of connected data can ultimately be seen in everyday operational decisions, from whether customer requests are addressed promptly, to whether teams can identify emerging problems and leaders have the information they need to respond.
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