Syrve Analytics Roadmap
Syrve Analytics Roadmap
Syrve is expanding its analytic suite to maximize output and provide business with the tools to respond to seasonal trends, business interruptions and even daily fluctuations in demand. Chains will leverage more of existing data for the benefit of scheduling operations and accurate forecasting. The roadmap for Capacity Management includes the following epics:
Staff Scheduling
Syrve WEB will receive an improved UI to complete rotas in a matter of minutes – not hours. The schedule will account for labor contract terms, skillset, age, and legally binding requirements, such as duration of rest breaks. Optionally, resources will be allocated automatically based on the user-defined business rules, which may alter based on the regional regulations or local commitments. Having a single shared view of the team, shifts, vacations, sick leaves, breaks and the ability for the employees to swap shifts will make external communications unnecessary. Staff Scheduling will evolve from a shift calendar into a powerful tool to plan human resources and optimize salary budget.
Equipment Capacity
Saturday morning, 9:00. You are taking a ride out to the country with your friends. To avoid traffic congestion on the exit from the city, one of your mates undertakes to order pizza and snacks for all the band. In 30 minutes you stop at the drive-thru window to learn, that your 7 pizzas have just made it into the oven a few seconds before you pulled in. The drive-thru attendant may at best make apologies, but this lose-lose situation will likely tilt your attitude towards the pizza restaurant round the corner.
With Syrve WEB, they are ready to proactively upscale equipment and respond to exceptions in daily operations in a way that the resources are distributed uniformly and the environment remains stress-free.
Skill Tracking
Syrve WEB is designed to adapt to operations with diverse team compositions. With the upcoming release, the managers will be able to create a taxonomy of skills and edit employees’ profiles based on ad-hoc upgrades or regular performance reviews. The skill model will be factored in by the scheduling mechanism and yield a semi-finished plan that is ready for review and approval. Collaterally, this will eliminate unnecessary communication in external messengers and help managers keep staff with the minimally required skill combination.
Courier Tracking
For quite a fraction of orders, delivery lifecycle does not terminate over the countertop. This is even more true for cloud kitchens. Produced items have to align with distribution. For this purpose, forecasting model in Syrve WEB will be enriched by transit times of own fleet and external delivery services.
Stock Forecasting
Syrve WEB offers basic forecasting model which uses recent purchases, current stock and sales for the past 10 days. This model does perfect job when it comes to short-term planning, yet does not account cycles, seasonality, irregularity - components which are intrinsic for well-established businesses with sales history stretching over 10 days. This leaves space for assumptions, and forecasting falls short of accuracy where planning time-frame includes holidays or any other events yielding outliers in sales data. In response to the customer requests, Syrve adds algorithm, which will provide higher confidence levels and will be configurable per store, per chain, per product. We believe, that data-driven decisions shall be backed by strong analytic tools.
Principal Component Analysis
Syrve suite of applications offers customizable reports that run over a wide array of data. Some correlations may be unobvious, e.g. a combination of gender and expenditures at a specific time of day may be viewed as a single component and tested against other variables, e.g. if this component holds consistent regardless of location.
Principal Component Analysis is a way to explore data in a more compact way rather than through browsing sales history, customer data, recipes in quest of business insights. Additionally, Syrve aims to provide tools that enable managers extract and transform data in a uniform interface, making export to 3rd party applications unnecessary.
Menu contribution margin
Contribution margin is one of the most important metrics to track the difference between the selling price and the food cost of each menu item. This way you may slice data to view stars, cash cows, dogs and questionable items. In addition to Price Dynamics report, this tool may help build and test hypothesis. This is where A/B testing comes into play.
A/B Testing
Fabula Coffee is an upscale coffee chain with locations in the western United States of America. The past few years have resulted in stagnant growth at the coffee chain, and a new management team was put in place to reignite growth at their stores. The first major growth initiative is to introduce gourmet sandwiches to the menu, along with limited wine offerings. The new management team believes that a television advertising campaign is crucial to driving people into the stores with these new offerings. However, the television campaign will require a significant boost in the company’s marketing budget, with an unknown return on investment (ROI).
Additionally, there is concern that current customers will not buy into the new menu offerings. To minimise risk, the management team decides to test the changes in two cities with new television advertising. Denver and Chicago cities were chosen to participate in this test because the stores in these two cities (or markets) perform similarly to all stores across the entire chain of stores; performance in these two markets would be a good proxy to predict how well the updated menu performs. The test ran for 12 weeks (2016-April-29 to 2016-July-21) where five stores in each of the test markets offered the updated menu along with television advertising.
A/B test is exactly the type of tool that helps test a the hypothesis, i.e. sales in Denver and Chicago versus the past two years of sales overall. Observations extracted from the experiment help come to decisions regarding menu composition that best tailors to customer demands.
For Fabula Coffee, the updated menu clearly has had an effect upon margin above the expected 18%. The results of the A/B test show that in the Central region the sales saw a 45.9%, and in the Western region the sales showed a 48.4% increase. Western region Central region There is a clear increase in sales starting from July that may be seen in both test and comparison periods, which may be a matter of seasonality, but the with the new menu offerings it becomes significantly steeper.
