Why Data-Based Algorithms Are Key To Business Survival

Business IntelligenceData Storage
microsoft analytics, data science

Michael Feindt, founder of Blue Yonder, says businesses that fail to implement data-based algorithms will die out

Millions of decisions are made every single day in businesses across the globe. In a supermarket, for example, managers have to make large numbers of decisions, from stock levels to pricing and offers. It’s incredibly difficult for a store manager to make accurate decisions consistently.

Many of these decisions are operational and can be driven by data; they do not require human insight, only strategic oversight. It is possible to automate these frequent decision using data science and algorithms, leaving employees to focus on the jobs they are trained and hired to do, whether that’s providing a superior customer experience, or innovating.

Finding value from your data

Data can help make decisions, but whether you have a terabyte or a kilobyte of data it is only valuable if you can draw insights from it. More than that, to get real value out of your data you need to utilise statistics and science to predict outcomes from data and automate business decisions.

According to Gartner, 2016 is ‘the year of the algorithm’. This means companies will be valued not just on their data assets, but also on the algorithms that turn this data into actions to save money and improve service. It also means that those companies that do not begin using algorithms will be left behind, missing out on operational efficiencies and improved customer experience. Only through algorithms can you collate actionable insights, automate operational decisions, and create transformative value.

data-breachChoosing an algorithm

A good algorithm answers questions from data that has been collected and uses it to create a series of models to predict the future and make decisions. Once you have applied algorithms to these key processes, the next step is to automate them. Automated processes based on algorithms can be applied in a range of industries – one example is retail.

Algorithms can be used to automate replenishment to ensure that companies don’t overstock or run out of stock, thus reducing waste and improving customer satisfaction. With British supermarkets recently pledging to cut food and drink waste by one fifth by 2025, algorithms will play a key role in achieving this goal. By accurately predicting demand for individual products at different times in specific stores, retailers can ensure they have enough product in stock but not too much. This is crucial for food and drink retailers where fresh produce has a limited shelf life or for popular products tied to key retail dates such as Valentine’s Day or Easter.

They can also be used to optimise pricing: In fashion, if an item doesn’t sell as well as thought, an algorithm can function to change prices on individual items throughout the season so the retailer doesn’t have an abundance of stock left at the end of the season that they are forced to throw away or sell off at a loss.

Removing gut-feelings

Automation and digital perspective capabilities help to take away the need for ‘gut feel’ based decision-making. Sophisticated algorithms can take into consideration weather, promotions and events which a basic spreadsheet-based system can’t factor in.

Removing the gut feel decision-making process also saves store managers a significant amount of time. Companies expect staff to forecast demand of product, orders, scheduling, labour and pricing, resulting in hours spent every day on admin tasks trying to do predictive analytics in their heads. Ultimately this is not something they are fully trained to do. By automating these processes, employees can return to focusing on their core capability. Store managers get back to ensuring they are delivering the best possible customer service..

Automation is simply taking all the monotonous decisions away. It still requires monitoring and managing but managers can concentrate on the strategic development and achieve better product availability, better forecasting and better staffing levels.

By adding in automated algorithms to decision-making, businesses become much more efficient. In automating replenishment, one German retailer delivered results of:
• €20m less waste
• €5m capital savings
• €5m efficiency savings
• 20 percent less out of stock because the right products were in the right quantity at the right time
• Out of stock issues were reduced from 6 per cent to 0.5 percent

Become data driven

It is crucial for businesses to become data driven, but data on its own is not enough. If you are still talking about just big data then you are missing the point – without algorithms big data is meaningless.

Those businesses that use technology to become more efficient will ultimately survive and thrive in the competitive market place.

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