Smart companies realize that analytics technology needs to be at the core of their business models. One of the most important ways that analytics can help companies thrive is by improving their logistics.
Analytics Technology Helps Companies Bolster their Logistics Strategies
If you were cryogenically frozen twenty years ago, upon awakening, you’d probably be more shocked to learn that you can place an order on the internet and get it the same day, than you would about the world’s billionaires attempting to conquer space.
You would also discover the big data is at the heart and soul of modern organizational practices. More companies are using data analytics to optimize their business models in creative ways. This is particularly true with logistics processes. The IoT has helped improve logistics, but big data has been even more impactful.
Indeed, shipping and logistics operations have come a long way in recent times, so much so that Finances Online claims top-tier management of the supply chain “isn’t just believed to be one of the top drivers of customer service improvement. It is also a case of business survival”. This wouldn’t have been possible without more companies investing in data analytics.
Some of the ways that data analytics can help companies improve their logistics include:
- Optimizing transportation routes
- Improving shipment schedules
- Reducing errors with delivery and pickup
On the journey from the click of your customer’s mouse to them opening the door to their delivery, convenience and efficiency are big factors that determine whether consumers will come back to you. For one, ensuring that delivery is as swift as possible is at the heart of current consumer expectations.
Analytics technology has been invaluable for improving the customer experience. Companies can identify transportation issues that lead to delays, find employees that are prone to make mistakes to retrain them and better track inventory with the use of data analytics.
But what else can firms do to make sure their operations are well-oiled? How can data analytics help with these other processes?
We’ve narrowed down the key strategies modern companies are using to enhance logistical management with data analytics technology.
Vertical integration is by no means a new concept, but it’s all the rage these days. As Investopedia spells out, this refers to when a company “streamlines its operations by taking direct ownership of various stages of its production process rather than relying on external contractors or suppliers”. In short, involves a business acquiring or creating its own production line and supply chain.
Cutting out the middleman allows companies to reduce their fixed-costs per unit, in what is known as economies of scale or diminishing marginal costs. Vertical integration optimizes operations for efficiency, and as the Balance suggests: “a company that’s vertically integrated can transfer the cost savings they create to the consumer” — although this comes at the price of a sizable initial investment. Alternatively, lower production costs mean that you can lower prices to incentivize more customer purchases.
Analytics tools make it easier to make better vertical integration strategies. You can mine data on potential supply-chain partners to make sure you aren’t acquiring a business that is not efficiently run. You can do this by using web scraper tools to collect data from company review websites and financial information on the company if it is publicly traded.
The next best bet for those who cannot immediately establish their own distribution is through stronger collaboration with courier companies. Courier service CitySprint, for instance, has “34 dedicated hubs across the UK”. Using such a service allows companies to emulate the perks of vertical integration by having localized distribution networks, enabling them to offer services like same-day delivery. As a result, a firm that is unable to achieve full vertical integration straight away can still meet the current consumer expectations elevated by e-Commerce giants like Amazon
Again, you will want o use data analytics to make better outsourcing decisions by collecting data on potential contractors.
2. Rationalizing SKUs
Analytics has also made it much easier to track inventory. This is often accomplished with the use of SKUs.
In the definition given by BigCommerce, “Stock Keeping Units [SKUs] are unique alphanumeric codes used by merchants to identify product types and variations”.
These are used by online companies to manage inventory, warehouse logistics and item specs with the use of inventory management systems with sophisticated analytics features. Your average supermarket will have, for instance, 15,000 of these — compared to the fast delivery services that use micro-warehouses and centers, and only have around 500-2000.
In simple terms, rationalizing SKUs means deciding whether the selling of specific products ought to continue. This way, businesses can streamline their offerings and reduce the overall complexity of their operations through the use of analytics.
While it might seem the more sensible choice is to have a diverse range of items for customers to choose from, holding too many SKUs can complicate logistics. If you have an excess of suppliers, data or you need greater amounts of storage space, this can make inventory management increasingly difficult and hamper the efficiency of deliveries.
Optimized inventory management
ShipBob clarifies that large retail companies use analytics tools to “keep track of all inventory in their large fulfilment centers and easily locate each SKU, so they can be accurately picked, packed, and shipped as orders are placed”. A popular analytics solution for this is through warehouse management systems (WMS), that organize data, including photos and other information, for fast retrieval.
By eliminating unnecessary SKUs at the delivery stage, businesses can limit back and forth communications with other parties like suppliers, as well as storage requirements, time and energy needed to create and package products that could be used in other parts of production.
The immediate perks of integrated business software revolve around efficiency, which is crucial for meeting customer expectations through the use of analytics technology. Most firms will rely on at least one or two business-critical platforms (such as digital banking, online shopping carts and/or cloud-based data storage), but any failure often results in a drop in productivity and revenue.
For instance, the inability to provide proper transaction information (such as receipts and invoices) due to loss of data will damage a company’s reputation. To insure against this and other issues, more and more firms are turning to software and communications integration to reduce business-critical risks.
One of the perks of integrating software solutions is also the reduced risk of these scenarios occurring. Akibia argues that software integration helps track communications with clients, so that “you can efficiently resolve as soon as possible. The quicker you address your clients’ queries and issues, the more favorable view your clients will hold about the organization”.
In logistics, a popular route to achieving better delivery results is through what’s known as carrier integration. While vertical integration consolidates the entire logistics process, carrier integration focuses on managing fulfilment processes and shipping data through a unified software and digital control center.
Once the shipper provides the location of origin and destination, the integrated software can identify what services are needed for each delivery and select the best packaging and carrier. This allows for the best possible response times since these processes are automated, saving time and user effort as well as eliminating the hidden costs of shipping execution.
Analytics Helps Companies Improve their Logistics
There are countless benefits of analytics in business. One of the biggest benefits is that data analytics can improve your logistics strategy. You should follow the guidelines listed above.