Restaurants have gotten smart, in the technical sense of the word. It’s increasingly unlikely, for instance, for a refrigeration issue to occur overnight without a temperature alert being sent to someone’s phone. Managers are using scheduling software to slash time devoted to shift-building. Financial teams are monitoring inventory management systems to reduce waste and limit needless spending. And the customer is experiencing value added services through the use of mobile apps and on-site tabletop devices.
One area where most restaurants aren’t quite as smart, however, is in having a plan to support the technology itself. Most restaurant groups are not yet leveraging the staggering volumes of data available about the causes of downtime, outage patterns, and preventative maintenance opportunities for the many systems they have in service.
Unfortunately, the maintenance models employed by most restaurant operations are not well suited to collecting such information. Thus, the search for business intelligence about the IT hardware stack begins with a new maintenance paradigm.
The Status Quo
The more integral technology is to daily operations, the more vulnerable a location is when that same technology fails, and downtime occurs. The technology-reliant customer experience suffers and staff time is redirected to troubleshooting. This is particularly true under the status quo model of IT hardware maintenance.
In default mode for restaurants, various technologies are installed, vendors each provide support for their own products, and on-site managers, servers, and other staff are simply left with a list of manufacturer contacts for when systems act up. The downsides of this approach are numerous:
- Loss of guest focus—Customer care suffers while a manager, often aided by a supposedly “tech savvy” team member, is consumed with troubleshooting. When issues occur during peak hours or when staff is stretched thin, the impacts on basic service can be severe.
- Lack of customized problem solving—The original equipment manufacturer (OEM) has minimal understanding of the environment in which the product is deployed and can struggle to offer clear troubleshooting assistance.
- Increased operational expenses—These factors reduce diagnostic accuracy and increase the likelihood that functional hardware will be slated for field technician attention or returned to a repair facility. Either can increase costs and downtime.
- No data gets collected to prevent future failures—Nothing about the support event or its outcomes is made known beyond the location. Every outage is treated as unique, without the benefit of previous experience.
Achieving Data-Driven IT Maintenance
The most forward-looking restaurant groups are concentrating on data collection to drive business intelligence on the IT hardware stack. There are two primary ways to do this:
Leverage a centralized IT department, enhance the OEM feedback loop regarding failure diagnoses and break/fix results, and incorporate the data into a business intelligence system. This generally requires negotiation of information-sharing mechanisms as part of contractual service level agreements with each vendor.
Turn to a single-source maintenance outsourcing provider capable of delivering multivendor support and supplying the business intelligence analytics to drive insights.
Either way, once information is at hand, restaurateurs typically find that acting in a data-driven manner becomes easy. Well-designed analytics tend to indicate an appropriate response.
For example, a restaurant group could review time-to-failure reports and discover that the kitchen ordering system frequently experiences a key outage after three years in service. Anticipating this downtime, executives can implement preventative maintenance or upgrades. By the same token, if tabletop hardware repaired for the third time usually breaks again soon thereafter, decision-makers can choose replacement at this stage instead.
Long-term maintenance information can also inform technology acquisition, because the cost-benefit becomes more apparent. Sometimes, “penny wise but pound foolish” choices are revealed, as when a low-cost solution results in a higher total cost of ownership (TCO) than a better-quality alternative. By reviewing vendor track records, restaurateurs can avoid buying from OEMs with significant rates of manufacturing defects, lackluster warranty follow-through, or other problems that compromise performance, reliability, and cost-efficiency.
These and other adjustments are possible but only if the data is collected in the first place. That cannot occur if individual locations bear the brunt of the IT maintenance burden. Restaurant groups that shift systems troubleshooting and ticket management away from individual establishments not only pave the way for business intelligence and optimization efforts, however, they also refocus teams on delivering the high-level customer service on which hospitality venues thrive.
