This article originally appeared on the BeyeNETWORK
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To most of us, running a pizza restaurant chain may seem like a straightforward and relatively simple business. As we enjoy our veggie supreme with extra cheese pizza, we don’t think about what it takes to make the pie to our satisfaction and deliver it within a reasonable time, every time we order it. However, in the effort to consistently meet – if not exceed – our expectations, behind-the-scenes business processes and the data to support them are more complex than we tend to think. At one major pizza chain, business intelligence provides the key performance indicators that help managers focus on improving operational efficiency and customer satisfaction in a competitive market.
For our client, a nationwide chain of a few thousand restaurants, rapid growth in recent years had increased the demand for timely information. Unfortunately their legacy systems were not able to keep up. Their systems were cumbersome to maintain and suffered from data integrity issues. Information was not available early enough, and data discrepancies resulted in low user confidence. Store operators and managers spent a lot of their time gathering data, which left less time for running the business. As a result, many aspects of the business were not examined often or very thoroughly. Therefore, opportunities for improvement were not addressed.
Our client needed to provide actionable information daily to operational management. The business objectives were:
- To understand and reduce the cost of operations, and
- To improve on the high level of customer satisfaction for which the chain had become known.
To address these two key areas, a range of performance indicators needed to be delivered on a daily basis, for each restaurant location across the chain. Speed was of the essence: even though restaurants on the west coast closed an hour or two past midnight, data had to be aggregated and performance indicators calculated by the start of the next business day at the corporate headquarters in the eastern U.S. time zone.
In considering the technology options, an online analytical processing (OLAP) software tool offered the best promise of meeting the needs of a wide audience and delivering consistent information quickly. With this approach, business data could be aggregated rapidly and uniform performance indicators calculated for each store location as well as peer group aggregates (by designated market area, franchisee, corporate-owned vs. franchised, etc.). Supported by consistent data from the point-of-sale (POS) system and data warehouse, theOLAP solution was to serve an audience that includes operations vice presidents, franchise operators, corporate finance, risk management, human resources and, of course, the company’s senior management.
The initial phase of the implementation was critical to the project’s ultimate success: achieving consensus among the various principal user groups as to which performance indicators to include and how they should be calculated. Discussion and negotiation led to prioritization of the application’s content. However, it was clear that in the future as the business evolved and more data became available, new information would be added and some indicators changed or dropped. The design of the OLAP application had to be flexible and extensible without sacrificing performance.
A range of operational data is brought into the OLAP engine, where several dozen operational performance indicators are calculated. In alignment with the project’s high-level objectives, two broad categories of performance metrics are available: financial (including loss prevention) statistics and customer satisfaction indicators. This information is captured for all stores daily and then aggregated to week, month and year levels. Year-over-year “comp” store reporting for all metrics is available.
Financial metrics include:
- Orders and sales (actual, comparable and budget)
- Delivery vs. carryout mix
- Ticket dollar average
- Food cost
- Labor hours and cost
- Delivery mileage cost
- Menu mix (quantity and percent)
- “Zeroed-out” orders
- Deep discounts
- Cash over/short
Customer satisfaction metrics include:
Average “make” time
- “Out-the-door” time
- Deliveries per run
- Customer complaints
- “Secret shopper” results, such as:
- Number of rings when calling to order
- Average hold time
- Customer service politeness rating
Of course, having great statistics in an OLAP engine is of little value if the people who need the information can’t easily get to it. For analysts at corporate headquarters, the OLAP tool’s spreadsheet interface has proven to be very handy for developing standard reports as well as for ad hoc analyses; but not everyone is a spreadsheet jock, especially those whose day-to-day work is to make and deliver pizzas.
Our client recognized that field managers and store operators should be focused on running the business, not running complex queries or spending time defining reports. A Web-based user interface that requires minimal training was deployed and rolled out company-wide. Performance indicators, grouped by category, are available in a “briefing-book” format. With the intuitive interface, users in the field can even create their own reports, resulting in a self-service environment that was accepted enthusiastically. The company’s chief operating officer commented, “This is a great, timely tool that provides users with the ultimate in customization. We couldn’t run the business without it.”
The application is providing users with more reliable and timely information while enabling the company’s IT department to do more with the budget and staff they have. Performance metrics for all restaurants across the country are available by 9:00 a.m. ET the next morning. The application is easy to learn and use, and users have embraced self-service reporting. The time and effort of operational management are now focused on what’s important to running and improving the business.
As for concrete benefits, the phased rollout illustrates the degree of impact the application has had on the business. The organization that manages the corporate-owned restaurants was given access to the new application before the franchised store operators. After several months, the corporate-owned locations outperformed the franchised restaurants by 2 to 3 percent in most performance measures.
Specific gains the pizza chain has seen include:
- Order completeness has improved significantly
- Out-the-door time has been reduced by almost 10%
- Overall customer satisfaction scores are higher
- Financial savings have been realized from improved collection of receivables and elimination of unjustified charges
- Operational summaries that took managers days to prepare are now done in minutes, freeing up time to address business issues
- The cost of supporting store operators with information has been reduced
Operational business intelligence is very effective when intelligently deployed and used by the organization. In the competitive and often narrow-margin restaurant business, business intelligence can help keep the “dough” rising, whether you serve pizza or any other cuisine.