Q, A better way

Typical systems implementations require vast amounts of time and money to both set up and maintain. Well with Q, we’ve created a better way. Where other systems typically require two to three years to be fully functional, our Agile Customer Experience (ACE)™ Implementation Methodology follows a phased implementation that lets retailers start seeing value within 6-8 weeks of beginning an engagement, and is fully functional within 6 months. That applies whether you are a global giant or a flourishing local retailer. Furthermore, in addition to being a tenth of the cost of traditional systems, there are rapid payoffs.

Affordable, low-risk licensing //

With Quantum Retail’s ACE™ methodology, there are significant reductions to upfront costs. In addition, we follow an affordable, low-risk annual term licensing model. This greatly reduces initial investment and risk. Because of the phased implementation, the entire solution quickly becomes self-funding.

Q in the cloud //

A key benefit is that the Q Engine does not necessitate an increase in the retailer’s IT department: the entire platform can either be run in the cloud or on site and is accessible from any computer. It can be hosted remotely or by Quantum Retail. Therefore there is no hardware investment required and only minimal involvement with the internal IT department is initially necessary to connect and operate the system.

Developing your business goals and strategies //

After all, every retailer has different requirements and a different set of goals for its inventory and business. Before an implementation even starts, our team will sit down with you and develop a detailed set of inventory goals and construct the strategies necessary for you to achieve them with Q. As part of this, Q was designed to be completely customizable from the outset. Q will continuously adjust to your changing needs and can automatically adjust optimal outputs to changes in business strategies over time without the need for system changes, recoding, or manually altering the system. The system does all the work itself.

Co-exist with the old and phase in with the new //

Cost savings and a quick implementation process are not the only concerns retailers have. Allocation and replenishment system implementations often require a ‘rip and replace’ of existing systems. Q allows the retailer to continue using its existing systems and to co-exist during the staged implementation. It can even permit those systems to continue running once the deployment is complete. The difference is that Q will take over most of the manual tasks previously carried out by the legacy system and will optimize the running of other tasks. Not surprisingly this option is viewed by many as an attractive alternative to ‘rip and replace’ actions.

A long term solution //

Once Q has been installed alongside the legacy system, it can operate in that way indefinitely. Alternatively, the legacy system can be phased out over time with Q replacing its functions. For example, a retailer might start by using Q to make decisions about longrange forecasting and initial in-season allocation of a certain range of SKUs in its stores, then increase that to all SKUs. They may then add in replenishment and store ordering activities, followed by forecasting and finally, time-phased order planning. Additionally, as Quantum Retail continues to grow, so does Q. As we develop new modules as the retail landscape continues to evolve, your business can easily adopt them too.

Your legacy data is simply history //

Traditionally, migrating legacy data from one system to another has historically been problematic when switching allocation and replenishment systems. Many competing systems require significant amounts of historical ‘seed’ data, often several years’ worth, in order to produce and maintain demand forecasts. This is an expensive and problematic part of the deployment, thus many retailers stick with the same vendor, even if they are disappointed with the old system.

Q, always present //

Q does not require significant historical data to produce highly accurate assortments, forecasts, order plans, allocations, and replenishment recommendations. In fact, Q does not store historical transaction data at all; Instead, it looks at the data as it’s provided, learns from it, and makes changes based on the latest information available. Because of this, Q has already proven itself effective in replacing systems from Oracle, JDA, i2 and proprietary solutions.

Say goodbye to the 20th century – Meet Q: The next generation in retail.