Improving final mile delivery operations with big data

by | Aug 25, 2020 | logistics

Understanding Big Data

Big data analytics is providing cutting edge companies with insights to develop qualitative and quantitative operations improvements, bringing contextual intelligence through the supply chain and major improvements in last mile deliveries. Clients are creating vast amounts of data which is translated into practical delivery business insights that can be applied to optimize logistics processes. Organizations can capitalize this information in order to create more personalized customer experiences.

As Brittan Lad, Amazon executive, states in this interview by ORTEC;

“I can’t stress enough the importance of leveraging analytics to gain insight and uncover hidden patterns related to processes, customers, and markets. Simply put, Big Data is a must-have.”

But let’s ease this. We can divide Big Data Analysis in two fundamental parts;

Big Data – Information and statistics about a business that are gathered and processed under three main concepts;

  1. Velocity: The information is captured in real time.
  2. Variety: Data is variable and depends on factors like time, context and volume.
  3. Volume: Better decisions are taken when we can evaluate a higher volume of right information.

Analysis – The use of mathematical and statistical models to give a purpose to the data in order to make operational decisions about a business opportunity or issue we can tackle.

Even though companies have relied on tools and techniques for many years to make decisions based on relevant information, with the rise of the digital consumer these tools become obsolete, and new types of data are needed. The methods used to gather information and analyze it have evolved, and so did the tools and process, which have changed over the years to bring a new era in the way managers can improve their daily operations.

Big data analysis can be applied in a vast amount of areas in the supply chain and logistics process, but one in particular has gained the attention of retailers, transportation companies and CPG services – the last mile delivery.

How Big Data analysis can improve your last mile delivery operations

Last mile deliveries is one of the logistics areas where big data can have a real impact on daily operations. It offers the opportunity to change and improve internal processes and better control external factors, from a business as well as customer perspective.

Impacting on the Business Operational Efficiency

For managers the use of data can be beneficial in improving three operational areas: 1. Increase levels of transparency in last mile delivery processes: Data can show pain point in last mile operations like communications problems during delivery, unexpected issues or delivery fail statuses.These are common problems in logistics companies, mainly due to low data availability which can help solve these problems real-time. 2. Costs and Resources Optimization Logistics and transportation companies are subject of external factors that affect directly their cost structure, such as changes in oil prices, traffic jams, insurance costs or damaged products. Managers need the right tools in order to analyze the status of their delivery operations real time, and make decisions based on most recent information. 3. Improve Process Quality and Performance Planning and scheduling also play an important role in the day to day life of any supply chain manager, especially because these activities have a direct impact in the customer experience. Using big data analysis and real time data collection, managers can plan ahead in terms of demand and delivery efforts, schedule and optimize the transportation routes, improve the number of orders that are on time and minimize the cost of getting returned items, knowing that problems can be tackled and solved as they appear.

The Customer Perspective Enhancing Experience

On the customer side this data can be used to gain:

1. Customer loyalty and retention

A survey by Capgemini and Oracle found that 44% of business leaders identified maintaining customer satisfaction as a key concern, and the only way to truly understand what customer wants is by analyzing historical data. Every logistic manager should aim to create a supply network and distribution operations that seeks to maximize the client’s perception of value, especially when we talk about last mile delivery experience. This is important as 90% of dissatisfied customers will not do business with a brand that failed to meet their expectations.

2. Customer segmentation and targeting

Companies developing multi-channel strategies must be capable to define and target each segment from their client base. The creation of contextual information from the customer behavior, online and offline, is a key step toward optimizing logistics efforts in the last mile delivery experience. This is only possible with a correct analysis of customer data and information.

3. Customer interactions and personalization

Data analytics is key to identifying trends and ways to engage with your customers. As Aphrodite Brinsmead, senior analyst at Analyst Ovum, states – “Look at ways to connect the content with customer data so customers receive personalized information based on their preferences. By having information on typical customer journeys and support questions, the organisation can predict what information a customer needs,”

He also added that – “When knowledge management discipline is in place, companies can reduce their customer support cost by 25% or more.”

Investing in Big Data Analytics

Mining information today is something that requires an investment in technology that can give clarity and sense to your last mile operations. Logistics managers can no longer rely on insights from separate business data systems which deliver information a few days after received.

“Technologies allow companies to leverage and quickly combine structured, unstructured, and semi-structured data at such a rapid pace that data is available in a central repository that doesn’t require the traditional design that enterprise data warehouses require,” says Steffin Harris, From Paris-based technology consulting firm Capgemini.

Data analysis have turn organisations into proactive actors rather than reactive to industry and customer needs changes. Software and visualization tools that manage data and transform it into daily reports and dashboards for easier interpretation are a growing industry .

Technology has become an essential part of logistics managers that aims to create sustainable operations over time, where improving efficiency and customer experience is the only way companies can take advantage in such competitive markets.

Investment are necessary in order to gain complete visibility and capability to take action over the data and information we are gathering, but is an investment that most likely will have big returns.