McDonald’s and Wawa use predictive data in making wise business decisions

Have you ever tried to release a new product it is too good it could “hurt” your enterprise?

This might be implausible, but it was what happened to Wawa — a convenience store chain that runs over 750 locations in six states of East Coast. It introduced a flatbread breakfast sandwich that made everyone in the company excited about it. You can just imagine their sales taking off, and it sure looked like an apparent winner. However, Wawa eliminated it shortly after its launch. Wondering why? Read on.

Adopting Efficient Predictive Analytics towards Business Growth

For big companies, launching a new marketing strategy, product or service involves risks. The following questions may emerge:

  • Can the changes gather more and new customers?
  • Will current consumers like the changes?
  • Would these generate enough revenue after the implementation costs?
  • How precise can the effect/s of income be determined?

Applied Predictive Technologies (APT) — a software company that gives business analytics software — created to aid consumer-facing enterprises to lessen the risk of any new strategy by systematically testing the plan with a subset of customers, stores or employees.

By using predictive analytics, businesses can formulate and make better management decisions. Let’s take McDonald’s and Wawa as two of the latest enterprises that benefit from this form of data analytics.

Wawa’s Experience

As mentioned above, Wawa’s flatbread breakfast sandwich was a massive success. Consumers bought many sandwiches — thus, increasing the sales. However, at a closer look, its popularity brought doom to other in-store products, which seemed more profitable. And after APT’s assessment on its unfavorable effects on revenue, the flatbread sandwich was pulled out.

McDonald’s Case

APT is also the one behind McDonald’s most recent move to sell breakfast foods all day, aside from its support to optimize menus and diversify new meal offerings.

In this case, the software company used its system to track trials of all-day breakfast service. It then turned out that it both gathered in new consumers and resulted in existing customers to spend more each visit. The determination to launch an all-day breakfast service pushed the growth of its current quarter sales and aided in boosting McDonald’s stock price.

Exploiting Predictive Data to Your Advantage

If you want to reap the same favorable result for your company, better consider utilizing the power of predictive analytics. Here are some tips to get started:

1. Strategize a data-driven mood as part of your business culture.

To become a data-driven company, it cries out for changes, involving moving away from highest paid person’s opinion (HiPPO)-based decisions. Classic practices can be difficult to change, and a lot of organizations fall prey to the error of using data to rationalize decisions after a particular fact instead of using data to make decisions.

2. Put your investment into new technologies and professional data scientists.

Hire a software company for consultation or internal data analysts to analyze big data. It is worth it for studying your business data with the use of modern analytics tools. In fact, a Harvard Business Review study revealed that 33 percent of companies that use data-driven decision-making have 5 percent higher productivity and 6 percent higher profitability compared to their competitors.

3. Utilize the RACI matrix.

With the popularity growth and importance of predictive data analytics, companies have to adapt their decision-making processes to get the upper hand of the insights they garner. The difficulty in today’s business world is that the market and consumers dictate more agility and fast decisions. Meanwhile, the use of reliable data means that companies have to involve more stakeholder groups in the decision.

The RACI (Responsible, Accountable, Consulted and Informed) framework can be a useful tool for identifying and tracking all the necessary parties and their roles in making decisions.

4. Do not only depend on HiPPOs.

A lot of firms opt to develop a precise decision-making process that depends on the instincts and experience of senior leaders and consultants. There must be a common source of decisions: focus on data analysis and highly valuable outside expertise.

The Verdict

Making use of predictive analytics is a trend that is not going to fade away from the business world. It has proven to deliver favorable results for businesses — just like in the cases of Wawa’s and McDonald’s.




Applied Predictive Technologies