Operational Analytics: Unlocking Hidden Value in E-Commerce
E-commerce has become a major force in the global retail industry, accounting for around 20% of all retail sales worldwide, and it continues to grow rapidly. However, achieving success in e-commerce is not easy. As e-commerce companies grow, their operations become increasingly complex, with the added challenge of selling across borders, managing fulfilment with thousands of products, and delivering across different countries within a day. In this dynamic and challenging environment, customers expect a seamless experience, while investors demand high returns, making it crucial for e-commerce businesses to handle the various complexities of their operations effectively. Fortunately, e-commerce companies have access to a wealth of data that they can and should utilise to achieve operational excellence, leading to higher customer satisfaction and improved margins.
There is a significant impact on the table in e-commerce operations
However, the reality is that most of the data in e-commerce remains untapped, with a limited set of information actively used. Currently, e-commerce firms focus mainly on marketing and product data, in order to increase sales, and they do not adequately utilise operational data such as in logistics, fulfilment and customer service. This presents a huge opportunity for e-commerce companies to improve their operational efficiency with the help of their data.
By using data-driven operations management, e-commerce companies can achieve significant margin improvements - we estimate it at around 3-5% -, via the uplift of customer experience driven by quicker reactions to operational incidents. In turn, this leads to higher customer retention and reorder rates.
There are several functions where e-commerce companies can use their data to improve their operations. One such use case is fulfilment. By utilising their data, e-commerce companies can detect errors in stock information, identify products that may soon go out of stock based on sales data, and even granularly monitor warehouse employee performance. Category management is another area where analytics can be leveraged. Real-time monitoring of detailed sales and product data can help identify pricing errors, missing content elements such as pictures, and even competitor moves such as the start of a competing deal. Logistics is a third relevant area. By getting a real-time overview of picking, shipping, and delivery timestamps, as well as tracking which riders or third-party logistics providers are performing better or worse, e-commerce logistics managers can optimise their processes for maximum efficiency.
The effective use of operational data can lead to significant improvements in e-commerce operations, resulting in increased efficiency, higher customer satisfaction, and ultimately, higher profits. If there can be such a huge impact in utilising data to reach operational excellence in e-commerce, why isn’t that widely captured already?
4 key reasons why data is underutilised in e-commerce operations
We identified the following four key reasons behind the underutilisation of operational data in e-commerce.
1. Management may not have made operational excellence a priority for the company
Achieving operational excellence is challenging and requires a concerted effort from the entire organisation. If management is not fully committed to improving operational efficiency, it is unlikely that the necessary resources and attention will be given to utilising operational data. In the past, e-commerce companies were focused on achieving growth as the primary objective to stay competitive in the market. However, with the current state of the market, where growth is stagnating or even decreasing for some, e-commerce businesses must shift their focus towards improving their customer experience and margins to retain their customers. Therefore, focusing on operational excellence has become more crucial than ever for e-commerce businesses to stay competitive in the market.
2. Data is not accessible in the right format
Although data is available, it is often fragmented in different systems that e-commerce companies use, instead of being in a central data warehouse. Even if data is already centralised into a warehouse, it is often in the wrong form, which means that it may be not transformed into ready to use business format or may not be updated at a high enough frequency to make a proper use of it. In order to properly utilise data in e-commerce, it’s important to spend time and money on the data infrastructure as a prerequisite.
3. Data is not utilised in an effective way
Despite having access to data in the right format within a centralised data warehouse, a common error made by e-commerce companies is to use dashboards as their primary tool for data analysis. While dashboards are useful for providing an overview of data, they may not be the best tool for identifying and addressing specific operational issues. These incidents (or opportunities) usually lie deep at a granular level, therefore it’s very difficult to spot them by looking at dashboards. Furthermore, the earlier teams can identify these incidents, the less harm they’re doing - and dashboards are not built for real-time detection.
4.The value of utilising data is often fragmented
The potential benefits or value that can be gained from using available data are often difficult to capture. That is because operations rarely follow the 80-20 rule - but you rather need to work on a long list of long tail levers in order to add up to visible impact. To capture this, e-commerce companies need to invest in tech resources such as software or data engineers to build real-time automated monitoring and automation on top of their data. However, many struggle with a lack of tech capacity, which means that operational improvement ideas are often not prioritised. As a result, capturing the value of data in e-commerce remains a challenge.
What's operational analytics and how to implement it?
Assuming that the management has recognized the significance of operational excellence, and that some of the operational data is available in a centralised data warehouse, e-commerce companies can start capturing the targeted 3-5% margin improvement. But how to do that without overburdening their limited tech resources? The solution is operational analytics.
Operational analytics goes beyond static business intelligence and insights. With operational analytics, the focus shifts from simply understanding data to taking action on it in the tools that you already use to run the day-to-day operations. This approach activates data and generates real-time, automated actions, empowering even non-technical users to activate the data without needing software engineering skills.
It offers several common features that help businesses monitor their operational events and automate tasks to improve efficiency. One of the key features of operational analytics is real-time monitoring and alerting of incidents or opportunities, which helps businesses stay on top of potential issues and act quickly to address them. Another important element is routing, which enables automated notifications to customers or partners, the creation of tasks in ticketing or task management systems, and syncing of information to any other third-party or custom system using webhooks. Operational analytics also provides unique insights about triggered events, which helps businesses understand what happened and make data-driven improvements.
While the implementation of operational analytics may differ depending on the maturity of companies, we’ve collected 5 general steps that businesses shall follow:
1. Define use cases
Before implementing operational analytics, e-commerce companies need to define the use cases that will have the biggest impact on their operations. They need to answer two key questions: where do they see the biggest potential impact and for which use cases do they already have data available? This will help them prioritise and focus on the use cases that will drive the most value for their business.
2. Choose an operational analytics tool
Once e-commerce companies have defined their use cases, they need to choose an operational analytics tool that is suited to their needs. It's important for them to understand what key actions they want to take with the tool - syncing actions into other systems or communicating to customers? They also need to identify who will be the project driver in their company - someone in the data team or someone in the operations team? Based on that, different systems may be needed.
3. Connect your data
Connecting the data is the easiest step if e-commerce companies have chosen the right tool. The tool should have integrations with their existing data sources, making it easy to connect and access the data they need.
4. Set up use cases
With the data connected, e-commerce companies can now set up the first use cases in the respective tool. It's important to test at least 4-5 use cases in parallel to take the necessary learnings and ensure that they are capturing the impact. This will help them understand the effectiveness of the tool and make any necessary adjustments to their processes.
5. Iterate and improve
Finally, e-commerce companies need to constantly iterate and improve their use of operational analytics to capture the full impact. Given that operations are constantly changing, they need to regularly review and refine their use cases to ensure that they are achieving maximum efficiency and delivering the desired outcomes.
By following these steps, e-commerce companies can effectively implement operational analytics and achieve operational excellence within their organisation. Developing an operational analytics system from scratch would require significant effort, but fortunately with available SaaS tools, they can now seamlessly introduce such a system with a few clicks.
Flawless is the only operational analytics system designed explicitly for business operations teams. Unlike other systems, it can be used effortlessly by non-technical users, even without SQL skills. This system offers pre-built integrations with all major data sources and various types of destinations (e.g., communication channels, ticket management tools or even custom backends), making it easy to set up in just five minutes.
Are you interested in testing Flawless as an operational analytics tool? Request a free trial here.