Why Analytics Success Depends on People, Not Just Technology | Notitia
According to Notitia Data Analytics Consultant Guilherme Matte, technology is only one part of the equation when it comes to turning data into meaningful insights and informed decisions.
"It doesn't matter if you have a great tool if people don't know how to use it, interpret the results or maintain it," Gui says.
"Technology is important, of course, but it's only one piece of the puzzle.
“The people using it need to understand what they're looking at and feel confident using the information to make decisions, so the solution can deliver its full value.”
While dashboards, reporting platforms and analytics tools often receive most of the attention, Gui believes the long-term success of any analytics initiative depends just as much on the people using it as the technology itself.
Technology Alone Doesn't Create Value
Many organisations invest significant time and resources implementing modern reporting and analytics solutions. The expectation is often that once the dashboard is delivered, better decision-making will naturally follow. In reality, the journey is rarely that simple.
Successful analytics projects require more than connecting data sources and creating visualisations. They require organisations to understand their data, trust the information being presented and have the confidence to use it in decision-making.
One of the most rewarding aspects of Gui's role is helping organisations uncover insights they didn't know existed.
"I enjoy the challenge of solving complex problems, but it's also incredibly rewarding when you help an organisation see something in their data they weren't aware of before," he says.
"Sometimes you uncover trends, issues or opportunities that were hidden in the data. Seeing people gain a better understanding is a really rewarding part of the job."
"There are times when you start exploring the data and find something nobody realised was happening. Those moments are exciting."
For many organisations, the challenge isn't a lack of data. The challenge is creating visibility and understanding.
Understanding What the Data Is Really Saying
One of the most common misconceptions Gui encounters is that organisations need more data to make better decisions. In reality, many organisations already have access to the information they need. The challenge is often understanding what that information is telling them.
As organisations grow, data is often spread across multiple systems, teams and business units. Different groups may have responsibility for different datasets, making it difficult to create a complete picture of what is happening across the organisation.
This is particularly common in large organisations where specialist knowledge sits within individual teams, while the business questions that need answering often span multiple areas.
"We see organisations where one team owns the data and has a deep understanding of it, while another team needs that information to answer important business questions but doesn't necessarily have the technical capability to access or work with it," Gui says.
"That doesn't mean the expertise isn't there. Often the knowledge already exists somewhere in the organisation, but it's spread across different teams and systems.
"Part of the challenge is bringing those pieces together so everyone is working from the same understanding."
Gui says in these situations the role of analytics is to bring together data from multiple sources and create a shared understanding of what it is saying.
This leads to deeper investigation and insights that can help organisations improve processes, identify opportunities and make more informed decisions.
Bringing in an external perspective can also help, Gui says.
"Someone from outside has the flexibility and time to create connections between teams, systems and processes that aren't always obvious internally," he says.
"We have to look across the whole picture because we're trying to understand how everything fits together."
"Sometimes that fresh perspective helps uncover opportunities that might otherwise be missed."
Why Capability Matters
At Notitia, analytics projects often include a strong focus on knowledge transfer and capability development alongside technical delivery.
The people who will ultimately receive value from an analytics solution are the people who use it every day.
"They're the ones who will maintain it, use it and make decisions based on it," Gui says.
"If people don't understand how the solution works, how to interpret the results or how to maintain it over time, it can become harder for organisations to realise the full benefits of the solution over time.
"The real goal is making sure the organisation can continue benefiting from the solution long after we've finished the project."
This is particularly important for organisations looking to build sustainable analytics capability rather than relying on external support indefinitely.
By investing in training, documentation and knowledge sharing throughout a project, organisations can build confidence within their teams and create a stronger foundation for future analytical work. The result is not only a successful project outcome, but a more capable organisation.
For Gui, capability building is one of the most important outcomes of any project.
Once a solution is delivered, organisations need to be able to maintain it, understand it and continue evolving it as their needs change.
"It means it is important to build confidence within the team, sharing knowledge and making sure they understand how everything works,” Gui says.
"When that happens, the organisation is in a much stronger position to tackle future challenges on its own."
Building Trust Through Governance
Trust is one of the most important ingredients in any analytics solution. When people trust the data, they use it. Trust gives decision-makers confidence to act on the information available to them.
According to Gui, many reporting challenges can be traced back to inconsistent processes, manual data handling and a lack of governance.
"Once people start losing confidence in the results, it's very difficult to get that trust back," he says.
"If different teams are reporting different numbers, people naturally start questioning the information."
"That's why governance, consistency and agreed definitions are so important. They help create confidence in the data and confidence in the decisions being made from it."
This is why governed data sources, agreed business definitions and standardised reporting processes are so important. In complex organisations, data often originates from multiple systems, teams and business areas. Without common definitions and standards, it becomes difficult to create a complete and accurate picture.
"You need common business rules, common definitions and consistent standards across your data," Gui explains.
"Without that, you're trying to compare information that may not mean the same thing across different systems."
"The technology can bring the data together, but governance is what helps make sure everyone is talking about the same thing."
"Without those standards, it's very difficult to build a complete and reliable picture."
Strong governance helps ensure data is consistent, reliable and fit for purpose, providing decision-makers with greater confidence in the information they use. This is particularly important in healthcare, government and other complex environments where information is often drawn from multiple sources.
Why Manual Reporting Creates Risk
While modern analytics platforms continue to evolve, many organisations still rely on spreadsheets and manual reporting processes to manage important information.
According to Gui, manual processes remain one of the most common challenges he encounters when working with clients. As data volumes increase, spreadsheets can become difficult to manage, particularly when multiple people are responsible for maintaining information. Different versions of reports, inconsistent data entry and manual updates can quickly create confusion and reduce confidence in the numbers being reported.
Many organisations have experienced situations where different teams are working from different versions of the same spreadsheet, resulting in conflicting numbers and uncertainty about which information can be trusted.
"If something can easily break, eventually it will," Gui says with a laugh.
"That's not because people are doing the wrong thing. It's usually because manual processes are difficult to maintain as organisations grow."
"The more manual steps involved, the greater the risk of inconsistencies, errors and different versions of the truth."
While spreadsheets remain valuable tools, organisations often reach a point where manual processes become difficult to scale. This is where governed reporting processes, automation and data quality controls become increasingly important. By reducing manual intervention and introducing consistent standards, organisations can spend less time validating data and more time using it to support decision-making.
Creating Solutions That Last
One of the biggest mistakes organisations can make is viewing analytics as a one-off project. The most successful solutions are designed with long-term sustainability in mind. That means creating solutions that are scalable, maintainable and capable of evolving alongside the organisation's needs.
It also means ensuring internal teams have the skills and confidence required to continue building on that work long after a project has finished.
A successful analytics project doesn't end when a dashboard goes live. It leaves behind stronger processes, greater confidence in data, improved analytical capability and a foundation for future innovation.
"The goal is to leave organisations in a position where they can continue getting value from their data well into the future," Gui says.
"A successful project isn't just about solving today's problem."
"It's about creating a foundation that allows the organisation to keep building, keep learning and keep getting value from their data into the future."
Looking Beyond The Project
For Gui, one of the most important measures of success is what happens after a project is complete. A successful analytics project should not only solve an immediate business problem but also leave the organisation in a stronger position than when the work began. The goal is to leave organisations with the capability, confidence and governance required to continue evolving their analytics environment as their needs change.
Find out more about Gui and the Notitia team here.
