Customer Company Size
Large Corporate
Country
- Australia
Product
- Qlik Sense
- Qlik
Tech Stack
- Business Intelligence
- Data Analytics
- Data Integration
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Digital Expertise
Technology Category
- Analytics & Modeling - Real Time Analytics
Applicable Industries
- Finance & Insurance
Applicable Functions
- Sales & Marketing
- Business Operation
Use Cases
- Real-Time Location System (RTLS)
Services
- Data Science Services
- System Integration
About The Customer
Yellow Brick Road (YBR) is a finance company founded by Mark Bouris in 2007. Initially, the company offered planning, advice, wealth management, and home loans. However, it has recently rebranded to focus almost entirely on home loans. YBR operates as a national network of community-level financial services branches, with a vision to provide all Australians with financial solutions from a local perspective. The company has more than $50 billion in loans on its books and operates through 73 YBR franchises and a strong network of 1,300 brokers and growing, offered through the Vow Financial platform.
The Challenge
Yellow Brick Road (YBR) was struggling with their existing business intelligence (BI) tool. The company was initially using Excel for data analysis and reporting, which led to significant delays in data delivery. The sales teams needed timely information to make decisions regarding sales targets and strategies, but the company didn’t have insights into loans until they received the commission statements from the banks—a delay of around eight weeks from the time of the actual sale. The delayed insights were always a challenge in making informed decisions to improve the sales KPIs, and the stacks of Excel sheets received from the lenders in different formats didn’t help with a timely and meaningful presentation. The company then implemented an emerging reporting software, which was a step up from Excel and a step in the right direction. However, not having local technical support and the tool's exorbitant pricing made them lean towards a more established tool with a local presence.
The Solution
YBR decided to replace their existing BI tool with Qlik Sense, an enterprise-level tool that could help them become a data-driven agency. The company went through demos and pricing to ensure the platform they chose would be the best solution for their future. They found that Qlik was more affordable than they’d expected and would save them a considerable sum compared to their previous software. The company also appreciated the relationship with Qlik partner EMARK Analytics and the locally-based assistance. The migration process was completed in six weeks, thanks to the vast support network and Qlik learning modules. Qlik Sense uses sheets to structure their apps as opposed to cluttering everything in one sheet, which allows for better user adoption. The filtering feature of Qlik Sense also ensures that the user only sees the appropriate information, saving time and increasing accuracy.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Real-time In-vehicle Monitoring
The telematic solution provides this vital premium-adjusting information. The solution also helps detect and deter vehicle or trailer theft – as soon as a theft occurs, monitoring personnel can alert the appropriate authorities, providing an exact location.“With more and more insurance companies and major fleet operators interested in monitoring driver behaviour on the grounds of road safety, efficient logistics and costs, the market for this type of device and associated e-business services is growing rapidly within Italy and the rest of Europe,” says Franco.“The insurance companies are especially interested in the pay-per-use and pay-as-you-drive applications while other organisations employ the technology for road user charging.”“One million vehicles in Italy currently carry such devices and forecasts indicate that the European market will increase tenfold by 2014.However, for our technology to work effectively, we needed a highly reliable wireless data network to carry the information between the vehicles and monitoring stations.”
Case Study
Safety First with Folksam
The competitiveness of the car insurance market is driving UBI growth as a means for insurance companies to differentiate their customer propositions as well as improving operational efficiency. An insurance model - usage-based insurance ("UBI") - offers possibilities for insurers to do more efficient market segmentation and accurate risk assessment and pricing. Insurers require an IoT solution for the purpose of data collection and performance analysis
Case Study
Smooth Transition to Energy Savings
The building was equipped with four end-of-life Trane water cooled chillers, located in the basement. Johnson Controls installed four York water cooled centrifugal chillers with unit mounted variable speed drives and a total installed cooling capacity of 6,8 MW. Each chiller has a capacity of 1,6 MW (variable to 1.9MW depending upon condenser water temperatures). Johnson Controls needed to design the equipment in such way that it would fit the dimensional constraints of the existing plant area and plant access route but also the specific performance requirements of the client. Morgan Stanley required the chiller plant to match the building load profile, turn down to match the low load requirement when needed and provide an improvement in the Energy Efficiency Ratio across the entire operating range. Other requirements were a reduction in the chiller noise level to improve the working environment in the plant room and a wide operating envelope coupled with intelligent controls to allow possible variation in both flow rate and temperature. The latter was needed to leverage increased capacity from a reduced number of machines during the different installation phases and allow future enhancement to a variable primary flow system.
Case Study
Automated Pallet Labeling Solution for SPR Packaging
SPR Packaging, an American supplier of packaging solutions, was in search of an automated pallet labeling solution that could meet their immediate and future needs. They aimed to equip their lines with automatic printer applicators, but also required a solution that could interface with their accounting software. The challenge was to find a system that could read a 2D code on pallets at the stretch wrapper, track the pallet, and flag any pallets with unread barcodes for inspection. The pallets could be single or double stacked, and the system needed to be able to differentiate between the two. SPR Packaging sought a system integrator with extensive experience in advanced printing and tracking solutions to provide a complete traceability system.
Case Study
Transforming insurance pricing while improving driver safety
The Internet of Things (IoT) is revolutionizing the car insurance industry on a scale not seen since the introduction of the car itself. For decades, premiums have been calculated using proxy-based risk assessment models and historical data. Today, a growing number of innovative companies such as Quebec-based Industrielle Alliance are moving to usage-based insurance (UBI) models, driven by the advancement of telematics technologies and smart tracking devices.
Case Study
MasterCard Improves Customer Experience Through Self-Service Data Prep
Derek Madison, Leader of Business Financial Support at MasterCard, oversees the validation of transactions and cash between two systems, whether they’re MasterCard owned or not. He was charged with identifying new ways to increase efficiency and improve MasterCard processes. At the outset, the 13-person team had to manually reconcile system interfaces using reports that resided on the company’s mainframe. Their first order of business each day was to print 20-30 individual, multi-page reports. Using a ruler to keep their place within each report, they would then hand-key the relevant data, line by line, into Excel for validation. “We’re talking about a task that took 40-80 hours each week,” recalls Madison, “As a growing company with rapidly expanding product offerings, we had to find a better way to prepare this data for analysis.”