Impos Solutions innovates, cuts infrastructure costs by 90%
Australian hospitality point-of-sale provider slashes costs, improves performance, and innovates by moving to Oracle Cloud.
“The Oracle solution is not only 90% cheaper than AWS and 7 times faster, it provides a platform for next-generation hospitality solutions and data insights with partners like JOMO.”
Business challenges
The leading Australian hospitality point-of-sale (POS) provider offers fast and reliable software and hardware to a range of businesses like restaurants, bars, clubs, nightclubs, and cafes.
Founded in 2005, Impos has more than 2,500 customers across Australia, New Zealand, and the Pacific Islands. It also serves customers in the defense and oil and gas industries. The company sells Impos Plus for single-venue businesses and Impos Enterprise for multisite restaurant groups and multinational services organizations.
The company’s POS products support a range of critical business functions, including front-office and back-office management, stock and inventory management, payments, loyalty, and rewards. In addition, it has an ecosystem for connecting third-party contactless ordering and payment apps such as JOMO, Till Payments, and Banjo Loans.
On top of the core software feature, Impos’s products offer powerful data insights with an analytics platform to help venues manage staff, stock and inventory, customer rewards, and loyalty, as well as target offers more efficiently.
With the company growing at 20% to 30% annually, its volume of data was doubling every year, along with increasing speeds at which the customers needed to access that data. As a result, Impos had to rapidly change its data delivery to provide timely, tailored, and relevant information to its customers.
This was having a big impact on the company’s performance, cost of service to its customers, and the resilience and availability of the services.
Impos, which was using a hybrid model of AWS and a private cloud infrastructure, had to consider something different to improve performance while slowing down growing costs.
Oracle Autonomous Data Warehouse really stands out in the automation of data movement. And there doesn't appear to be a lot in the market that goes nearly as far in keeping your workflows simple and ensuring minimal disruption in your business or potential downtime.
Why Impos Solutions Chose Oracle
After evaluating AWS and Azure, Impos ultimately decided that Oracle Cloud Infrastructure (OCI) and Autonomous Data Warehouse were the best options.
Besides the scalability and ease of operations of Oracle Cloud Infrastructure, the simplicity of database and application migration helped Impos decide on Oracle.
In addition, predictable costs over the long term tilted the scales in Oracle’s favor.
Results
By moving to OCI and adopting Autonomous Data Warehouse, Impos has been able to cut its infrastructure costs by more than 90%. Time to load and to run reports is now 7X faster. The company is now able to do a lot more with data while also managing the environment with fewer resources. Impos can now make real-time, non-disruptive changes and updates. Before, administrators had to create change windows and outages.
The migration has also greatly improved the time to load and run reports. Customers can now use a far bigger data set to make their decisions and can go from volume-level information or daily base information down to transaction-level insights. In addition, businesses can attribute transaction-level information to a staff member and understand which staff members are upselling or who needs more training.
Also, using AI and machine learning, clients can understand what their customers do, when they visit, what they buy, and who they come with. Using all this granular data, clients of Impos can now build targeted offers for their customers, something the company couldn’t offer previously.
Impos’s clients can reconcile sales, stocks voids and tips in a matter of minutes, when those tasks used to take days before the migration. Clients also have increased accuracy using these multiple data sets to tie back to stock and inventory—all the way down to a milliliter decrement in a glass instead of a bottle.