How to Transform Your Financial Processes and Make Better Decisions with Data


Every company wants to move fast, but no one wants to slip up. To make the best decisions quickly, the only way to do it is with the right information. That’s why so many organisations are becoming obsessed with data.

But it isn’t data alone that will save your business. It’s the combination of data and technology, all the while aligning your people and processes. After all, even the best decisions will fail if they aren’t implemented or communicated correctly.


When it comes to the power of data, ANZ is among the true believers. We are an Australian multinational banking and financial services company headquartered in Melbourne. We have a proud heritage of more than 185 years as a bank. Today, we operate in 33 markets globally, including Australia, New Zealand, Europe, America, and the Middle East.

I currently lead the business intelligence strategy for the finance team at ANZ. With an educational background in accounting and finance, I have been with ANZ for more than half of my 17-year career. During that time, I worked with a variety of financial products, including global financial markets, institutional transaction banking, consumer credit cards, retail banking, projects, and shared services.

A Commitment to Data

ANZ demonstrates the commitment to data-based decisions in a number of ways. Our BI operation works most often in insights and analytics, forecasting, planning, as well as financial control. We have around 900 full-time employees and a dedicated systems team of 90 staff. Our unit is designed for agility, with 63% working in development operations and 37% focused on scrum squads.

Our overall goal is to transform the way finance operates. We want to improve the access to and presentation of information. These improvements will ultimately help us to better navigate data and make better decisions faster.

Want to make decisions faster? Improve the access to and presentation of information.

Our strategy is founded on three layers: data asset, presentation, and analytics. Each of these layers further has three key principles to anchor our long-term vision. We use these principles to serve as our north star, since we know that successful implementation requires more than just the data and technology. Without these shared points, it is nearly impossible to align processes and people.

I could go on for days about what these nine principles entail. But to summarise, our principles cover:

  • Having a connected, centralised database that is a single source of truth
  • Data structures that promote rapid speed of delivery and are easy to support
  • Designing interfaces with a focus on intuitive user experiences to embed high adoption rates
  • Having the right tools for the right purpose
  • Proficiency in methods to derive value from data
  • Constantly evolving and leveraging new technology to improve

A Qlik Story in Three Acts: Act I

Rather than provide cumbersome detail into our internal policies, I would much rather share a few stories about the impact of our data strategies. I believe this is a much better way to demonstrate the power of data-based decisions using the common thread of people and change.

As context for my first story, in finance we have over 6,500 people using more than 40 reporting applications in a mix of QlikView and Qlik Sense. The applications serve many different purposes, including financial analytics, expense management, customer profitability, and governance. Up to a few months ago, our most senior leaders were still consuming their repeatable financial information via emails and PowerPoint. They also continued to manually prepare and manage thousands of Excel spreadsheets.

This traditional reporting method continued so that they could receive their financials in the way they preferred. Some of them wanted hundreds of pages of tables while others preferred a two-page graphical update. Many reports were submitted with lots of commentary explaining everything, while others included only a short and sharp analysis. Managing change was needed, from engagement, readiness to adoption. 

To break bad organizational data habits, change often needs to come from the top.

We made progress when our CEO embraced, advocated, and supported the change. This leadership by example from the top reverberated down through the layers. Today, our senior leaders consume their financial information on the same Qlik Sense application with the same user experience.

People who are curious about the transition process often ask me about UX. They will wonder if we use ongoing FAQ sheets, training sessions, or other helpful tools. In my opinion, good UX is like a bad joke: If you have to explain it, it isn’t very good. If the user can use our intranet, complete online banking, and shop online, they shouldn't need further assistance. Simple intuitive applications using Qlik platforms make it easier to promote adoption.

As an example of the impact, our group CFO recently provided feedback that she used the tool twice while presenting to the Board of Directors. During the meeting, she was asked two questions and was able to answer both directly with the tool. If your data applications don't allow natural, real-time inquiries, you need to rethink your operation.

We can now provide reporting that is consistent where it should be consistent and tailored where the business drivers are different. The process is consistent, and we’re using technology to reduce operating risk. These advantages work throughout approval flows, user access management, archiving commentary, and key person dependency.

This is just one step, but an important one in our BI journey.

Act II: Using Qlik to Validate Data

My next story is about our analysts doing the insights and analytics. The internet is full of references and statistics on how analysts spend the vast majority of their time sourcing, joining, cleaning, and validating data. While these steps are necessary, they take away from the time to analyse, communicate, and influence decision making. Smart organisations know, however, that taking the time to get the data right is critical to the eventual analysis.

At ANZ, we prioritise getting the foundations right. As a large bank, we have many different systems feeding into the general ledger before they are consolidated into Hyperion as the finance source of truth. During our long journey with data, this is where most of our heavy lifting was spent. Our data story isn’t finished, but we have completed our domestic products, including home loans, credit cards, deposits, and business banking. We are also made significant headway through our institutional international products.

Part of the migration to better data management is understanding what kind of data in this environment is valuable for business modelling. We are focused on discovering data that can provide compelling insights and influence our business leaders to make fact-based decisions that improve performance. To be compelling, this information must be analysed using many interlocking variables so that the analysis is holistic. For example, it doesn't make sense to study the income of a facility without considering the margin driver, location, customer base, and offered products.

This is where the process gets tricky. How can you analyse multiple data points together when each point likely comes from a different source? Effective analysis requires a centralised source of truth created with minimal human intervention to reduce operational risk. Most importantly, the data must be structured and connected in such a way to allow common ground.

This is all fantastic, but many of our users don’t have tech or coding skills to access this data. At the same time, much of our work in bespoke analytics is testing, trial and error, and exploring various data options to form insights. That means we have to keep asking those with the coding skills for these extracts, which adds extra layers of handling and slows the process considerably.

This is where Qlik becomes the perfect tool for our purpose and the skill level of our analysts.

Qlik has features that speed up the process of exposing the data lineage. We are able to quickly discover where the data was sourced and how it reconciles to Hyperion. This provides immediate trust in the data and cuts down validation time. One of our analysts recently noted that investigating a business problem used to take us days to source the data and convert it into something consumable and trusted. Using Qlik, we can now complete our analysis within hours.

Act III: Lessons from the Data Change Drivers

So far, I’ve shared stories about our leaders and our analysts. What about those driving the change? Based on my experience, I have a few insights to consider for those that want to transform their organisation. First, it is best to focus on an agile approach where value is released incrementally. Unlike the traditional approach that seeks a big bang at the end, the marginal method allows customers to see momentum and provide fast feedback.

Last month our CEO asked for a change and it was completed by the next time he used the application. He believed it was very encouraging to see the change done so quickly. That kind of enthusiasm can spread to other units faster and more thoroughly than any marketing efforts by the BI unit.

The second lesson is that it’s important for our leaders to be invested. We were lucky to have a senior executive sponsoring the program, creating a healthy mix of top-down and bottom-up change. Starting at both sides and meeting in the middle allowed us to better manage resistance and keep the changes grounded in the organisation's overall purpose.

The third lesson is about boundaries. We had to be clear about our customers and not attempt to design a product for all people and purposes. Trying to be all things to everyone will almost always fail. Boundaries are formed in the design stages and incorporated into the UX. That allowed us to focus on flexibility in content targeted towards a specific list of financial and performance drivers.

The Way Forward

We are still on our BI journey, but are confident that we are making some strong steps in the right direction. Our infrastructure is in place and designed with the flexibility to absorb emerging technologies so we can remain at the forefront of business risks and opportunities. We are already watching fields like AI natural language generation, chatbots, predictive analysis, and automated forecasting.

Finance is keenly suited to benefit from the insights and speed that an excellent BI program can confer. ANZ has the need, foundations, and advocacy to create a fully data-mature organisation. And in the words of Richard Bach, “Any powerful idea is absolutely fascinating and absolutely useless until we choose to use it.” Luckily, we’re choosing to use it.