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One Profound Mistake With Your Retail Data?

by | May 29, 2017

One Profound Mistake With Your Retail Data?

You’re a demand-driven organization: A retailer or a grocery store or a restaurant. You have many employees.

For a long time now, you’ve been using traffic and POS data to make staffing and scheduling decisions …

But you’re doing it manually, using data dispersed across spreadsheets, across locations and people. Is your data being used efficiently and effectively to schedule employees? Or is it merely being categorized, teed up for misinterpretation and misuse by a busy manager?

This article is about the propensity for the latter among growing, demand-oriented enterprises. Organizations that could glean so much more from their data if they only allowed themselves to outgrow the status quo and automate.

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Manual Scheduling: The Pitfalls

In regards to data, the human element leaves plenty of room for error and oversight.

This makes it difficult, even impossible, for manual schedulers to consistently:

1. Schedule accurately to demand:

Your demand should take both your customers’ and your employees’ needs into account …

You want to understand and respond to traffic but you also want to weave the needs of your staff into the schedule. If you don’t, they’ll leave you.

You also want to adhere to the policies of your company and the laws of your state. If you don’t, you’re taking an incredible risk.

Striking that balance is hard to do if you’re using a spreadsheet.

2. Schedule by skill set:

Who’s a great salesperson? Who’s still learning? Who speaks Spanish? Who is your opener? Your closer? Who’s on the bubble?

Personal relationships help managers schedule better. After all, a productive sales floor is about skills, not bodies. But what happens if that manager goes on vacation? Or quits? Whatever the case …

If all that knowledge isn’t stored in a database, it goes with them.

3. Schedule to minimize overtime:

The butterfly effect is a concept predicated on the fact that small causes can have big consequences. The name is metaphorical: A tornado born out of a butterfly’s flapping.

The butterfly effect is a ubiquitous phenomenon. It exists everywhere, even in retail scheduling: A small manual change to an employee’s hours could force other changes past a threshold …

That’s when overtime comes into play and compliance laws enter the picture.

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Automated Scheduling: The Advantages

Consistent, fair schedules make employees happy and engaged, eager to do their work well. Customers love happy employees, people that are present and competent.

Their energy is good for business.

1. Fair schedules engage employees.

An algorithm can help big organizations:

  1. Forecasts labor demand by analyzing historic traffic and sales data.
  2. Schedules employees based not only on the hard data, but on the preferences of staff.

Modern employment is about balancing the needs of the business with those of the people behind it.

2. Engaged employees delight customers.

Happy, delighted customers are, in part, the product of engaged employees. Employees with a degree of control over their work-life situation (because those are the happiest ones of all).

Of course, other factors count towards the whole, but few perks breed engagement at work like autonomy and flexibility. Data-engineered schedules enable this (as well as the customer support it drives).

3. The business is legally protected.

Modern, automated schedules factor in regional compliance laws and regulations, ensuring that the business is doling out legal hours to employees.

No lawsuits.*

The Gist:

Retailers, grocers, restaurants, and other organizations driven by day-to-day customer demand depend on a consistent flow of data to inform their scheduling and staffing decisions.

Of course, the greater your head count, the more challenging it becomes to organize, analyze and apply the data efficiently and effectively, viably.

The antidote? Automation.

It’s time.

A modern workforce management solution will help you schedule employees more efficiently.

*Always consult an attorney about legal matters.

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