Using Data Patterns in a Retail Culture of Immediacy 

Retailers who have embraced digital disruption and transformed their businesses know two hard truths: consumer expectations can rise quickly; and no seller is safe.

Thanks to the “Amazon Effect,” consumers now believe that benefits like expedited, on-demand deliveries are the baseline for any online retailer. Consumers want more product choices, at a lower cost, delivered faster, with full transparency, from the moment they place an order. And when any part of this process goes wrong, they expect the issue to be resolved as quickly and as painlessly as possible without having to touch a phone.

In this culture of immediacy, niche retailers as well as online giants need to evaluate their organizational processes if they want to compete in the new digital marketplace. While small deviations from standard processes may seemingly have a marginal effect on business output, in reality they have a significant impact on a company’s overall efficiency.

The Data Advantage

E-commerce businesses that save time and money by operating more efficiently gain the upper hand. There’s no shortage of data that e-retailers generate since their processes tend to be almost exclusively digitized. In fact, more data has been created in the last two years than the previous 5,000. Sellers have a wealth of available information through digital transactions, but to leverage it they need the right tools in place.

Traditionally, retailers have hired management consultants to analyse and improve core operations, such as purchasing, logistics and production. This lengthy and expensive practice eventually uncovers inefficiencies, such as bottlenecks in delivery or unnecessary manual procedures. But at what cost? Consultants rely heavily upon the existing operations teams to collect data and provide context. This often disrupts everyday operations, which in turn, negatively affects overall output.

From Digital Traces to Transparency

Identifying issues in core processes is like finding a needle in a haystack. But that’s no cause for alarm. Fortunately, algorithms are powerful enough to help online retailers of any size sift through data and make informed decisions that benefit the customer, helping identify hidden patterns in the data. This is called process mining, which extracts anomalies in the data and pinpoints inefficiencies in core operations.

Process mining supports the analysis of business processes based on event logs. During process mining, algorithms are applied to event log data to identify trends, patters and details to help improve process efficiency. Often process mining is the first attempt to use this raw data in a structured way.

Every IT-driven operation leaves a digital trace and process mining leverages these “footprints” to provide an objective look into how internal processes are operating. Using this raw data, process mining reconstructs as-is processes and visualizes all of the digital processes in real-time. CFOs, logistics managers, heads of purchasing and other process owners can then use these insights to identify delays, bottlenecks and other causes of inefficiency.

For example, Philips needed to filter the most relevant business events on its e-commerce site to fully understand its customers. This was especially important for its global marketing team because Philips sells a wide variety of products including personal care, mother and child care, and household items. Accordingly, Philips implemented a combination of web analytics and process mining technologies to understand the end-to-end customer journey and proactively identify improvements within its overall marketing strategy.

The web analytics offered insights through known performance KPIs, whereas the process mining platform added two additional functions: it identified why the KPIs indicated underperformance and prescribed next steps for effective change. Inefficiencies in engagement were discovered in the combination of marketing channels used. Process Mining additionally revealed bottlenecks in the site interface that caused customers to abandon the site without making a purchase. This unbiased discovery process enabled the marketing team to visually filter and benchmark business-critical variables faster without any prior analytics expertise or questions in mind.

Any retailer that wishes to remain relevant in this digital age must first embrace the value of data analytics and then seek out technology solutions that enable them to put it to use. Improving efficiency will ultimately help online retailers give customers what they want, when they want it, with full transparency.

Alexander Rinke is co-founder and CEO of Celonis.