Realizing the Potential of Good Data
Create a list of the tech systems you currently use to run your company. Add to that list kinds of systems you want to implement. This simple exercise is becoming more complicated!
As restaurant technology (and technology in general) has changed during the past few years the landscape of systems you rely on to conduct your business has expanded and changed too. From contemporary cloud POS applications, to online ordering platforms, to third party shipping, to restaurant management, to loyalty, to proactive customer satisfaction there are tons of technology-based opportunities to enhance business.
Sources
/offline-pos-machine-you-will-need/
/benefits-of-pos-system-for-brick-and-mortar-stores/
/8-tips-boost-online-presence-for-fashion-brands/
These modern systems offer restaurant organizations with robust and new data sources. The information from each of these systems is important; nonetheless, real insight can only start with the data from each these systems working together.
But what are you searching for in this data? Where do you begin? How can you acquire the data lined up in a sense where data from many systems isn't hard to work with? Is this Big Data? All this can very quickly add up to a case of information fatigue.
At Restaurant Analytics Delivered -- Call us RAD -- we adore data! Multiple disparate sources continuously collecting information drive what we do -- we assist our partners realize the potential of the data and prevent data fatigue. Below are the guiding principles we use to help our partners together their data travel.
- Focus on good information before large data
While Big Data is a definable idea, it's a lofty objective. Like every obstacle it can be overwhelming to consider the end point as opposed to searching for discreet solvable measures to get you there.
The initial steps on your data journey ought to be directed at creating a rated and piled list of information priorities and information complexities.
By way of instance, transactional restaurant POS information is different than unstructured social data. Understand that both resources can be directionally right while human analysis of social data won't be as quantitatively precise as detailed transaction analysis.
See also
/knowledgebase/setting-up-your-outlets/
/knowledgebase/setting-up-your-register/
/pos-review-connectpos-versus-hike-pos/
Start looking for smaller wins and large time-savers.
- Create a culture of analytics
We often realize that there are a number of sources of fact for analytics within a company. Tied to the point above, a cultural change often needs to happen to change outlook on what analytics are and how your company uses them.
Begin with a single resource for fundamental operational metrics. Share and challenge definitions for even basic information points which are regularly review. Provide all levels of the company are the exact data to assess these metrics.
Buy-in from the top is critical, encourage executives to engage employees and share outcomes.
- Track the Perfect information for you
Restaurants have character and their data does also.
When there are probably metrics you want to track that lots of organizations look at, you might define them differently. You might also include metrics which aren't typical but are important for you.
Don't settle for reporting applications that boxes you into canned reports or metrics. You want to be nimble, to have the ability to modify your information definitions, and also to create new metrics readily.
- Research
All this information is at your fingertips -- now what?
Learn the systems and their granularity. Learn more about the origin systems, ask questions, understand how it is possible to find ticket level data in addition to daily, weekly, and period-to-date summaries.
Have you ever wondered about attachment rates of particular products, or COGS efficacy with your LTOS? Can you track visitors to labor efficiency through the day and contrary to scheduled labour? Now's the time to ask these questions and begin drawing correlations.
Related posts
/knowledgebase/create-adjustment/
/knowledgebase/open-a-new-shift/
- Evolve
By this stage in the journey you'll be ready to start getting to the buzzworthy themes of Big Data, Predictive Analytics, and Machine Learning.
In case you've been guided through your information travel appropriately it won't look quite as awkward as it did when you began. You'll have a solid sense of the sorts of information at your disposal, their efficiency within your information landscape, and the way in which your data sources fit together.
Statistically relevant models can be developed for numerous purposes such as identifying targeted advertising opportunities, better property selection, and perfect labor scheduling.
- Consider your information a tool, not the response
Systems and technologies will continue to change. While RAD prides itself on being an adaptable partner that can allow you to incorporate new systems and maintain data history as you grow, we think true silver bullet lies inside the restaurants at an operational level. Trust your operators, and give them the tools to enhance their performance and the guests' experience.
Our other sources
/knowledgebase/working-with-products-wip/
Comments
Post a Comment