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Customer experience, or CX, has always been not only a focus of much corporate attention but also the differentiating factor of most successful organizations. What has changed in recent years is the dramatic advancement in technology and fulfillment opportunities to improve the customer experience. However, it’s still rare to see CX directly related to supply chain operations in B2B commerce.
That’s a shame, because what goes on “behind the scenes” or “in the shipping department” dramatically influences the impression an end-customer carries away from their experience, even if it’s in the B2B, rather than B2C, realm. It’s critical to keep the customer experience in mind, taking into account each customer’s specific service requirements (delivery days, availability, return policies, etc.) and financial capabilities.
Moreover, it’s key to engage throughout the lifecycle of a customer order transaction. That includes dynamic production scheduling, proactive after-sales support, comprehensive customer feedback mechanisms, enhanced supplier collaboration for parts and components, and advanced data analytics and insights at all stages. Arguably, the bulk of what goes on is in the hands of supply chain operations and, with the rising predominance of online ordering, B2B customers’ interactions with manufacturers happen largely in the realms of supply chain.
The purchasing decision is reliant on establishing if the item is available (inventory management), securing available delivery speeds (from order fulfillment through delivery truck routing and tracking), and after-sales support (including dispatching maintenance engineers, and even reverse logistics). “Every organization is operating with some fundamental value proposition, and this informs what experience they will offer the customer,” says Girish Dhaneshwar, consulting leader, retail, consumer, manufacturing and logistics at Cognizant, the information technology and consulting company that specializes in deploying generative artificial intelligence (AI) and machine learning (ML) to improve business processes. “The question is: How do you ensure that your supply chain is structured to make sure you fulfill that intention for each and every customer in a diverse pool?” For example, you may want to provide customers with a wide range of equipment and services at the lowest cost.
In order to be sure you are delivering on that promise, you’ll be looking to achieve high operational efficiency in your manufacturing plants to keep costs low, while offering a wide range of choice, including the possibility of delayed customization/form postponement when appropriate and financially feasible. “So, you need to engineer for flexibility, including your sourcing strategy, production schedules, even design,” says Dhaneshwar. Or perhaps your value proposition is an outstanding service network.
That will then be built on business policies such as next-day or two-day delivery. “That’s going to inform your inventory stocking policy and how you structure your dealership network,” says Dhaneshwar. Another example is if a company wants to offer a range of fulfillment options — such as door-to-door, curbside, or direct to a distribution center.
“They’re all different. If it’s direct to a DC, that could mean rebranding the product; the process, and of course, the price offered to customers, is very different,” explains Dhaneshwar. “The best order management solutions today offer this.
They have the flexibility to manage those options.” One of the challenges all businesses face today is the rise in expectations of customers across the board, including B2B. The procurement manager ordering a thousand parts is used to getting detailed, accurate information about what’s being delivered to their home.
“Amazon spoiled consumers!” says Dhaneshwar. “They’re in the habit of saying if you click on this in the next ten minutes, you’ll have it on your doorstep by 9am tomorrow. The visibility that you can get into orders is phenomenal.
You can see that the order is being picked, then shipped, now it’s around the corner. That’s a world-class experience. The available-to-promise (ATP) is phenomenal.
The order management, the transportation network...
all of that is making this world-class customer experience possible. And this is now spreading to the B2B world. The expectations have been raised.
B2B customers are asking: Why can’t I have the same service?” Dhaneshwar argues that these raised expectations are forcing the need for superior supply chain capability, including the ability to weave multi-channel complexities (fulfillment, warehouse operations, inventory planning) into an integrated network. “It’s about translating the customer experience into both supply chain capabilities and policies. You focus on the end result and go back through each part of the supply chain to make sure that it’s jibing.
” Visibility of goods available-to-promise is one of the fundamentals, says Magesh Karthik Krishnamurthy, supply chain leader at Cognizant. Further back up the supply chain, that means excellent demand-sensing, and the ability to opt for postponement in the case of appropriate products, so that there’s minimal excess inventory. “For the chief supply chain officer, inventory is one of their key concerns, because there’s a significant amount of working capital locked up in it,” says Krishnamurthy.
“There’s always a push to optimize inventory and unlock capital.” That puts demand-sensing high on the list of priorities, because it allows companies to know how to adapt their supply chains to actual, near-real-time market changes. Krishnamurthy says it’s necessary to constantly plug into social media and multiple other sources of data to really get an idea of how the market is moving for certain products.
Dhaneshwar says one important development has been the revolution in technology presented by the appearance of sophisticated AI tools. “Technology has become such a differentiator. It’s opened up possibilities to drive customer experience into the supply chain,” he says.
AI offers the computational power to handle large data volumes from RFID, internet of things (IoT) and other types of sensors and sources of data, in order to enhance visibility and transparency throughout the supply chain. “The predictive capabilities of AI and ML give us the ATP accuracy that wasn’t possible 10 years ago,” Dhaneshwar says. AI has also brought major improvements to other operations such as procurement and service management, even energy management and sustainability metrics.
“Everyone’s under pressure because of sustainability regulations,” he comments. “Technology is very important in terms of driving the customer experience into the supply chain.” Krishnamurthy points to real-world benefits of AI-driven demand-sensing.
For example, one of Cognizant’s customers manufactures influenza vaccines, and they need to understand when ‘flu season’ is coming and what is likely to be the level in each region. Using AI, the company can derive demand signals that predict where ‘flu’ is going to spike in the next two or three months, giving the vaccine manufacturer time to produce the right amount of medicine, and get it to the right regions. AI’s demand-sensing capabilities also benefit industries where postponement is critical, especially in retail, where there tends to be a shorter lead time.
Customers can now confidently delay the actual assembly and finalization of a product, depending on accurate predictions of market fluctuations. As a result, Cognizant is seeing more of its customers being able to deploy postponement intelligently. “With generative AI, demand-sensing is better than, say, five years ago,” says Krishnamurthy.
“It’s opened the doors for more organizations to adopt a postponement strategy. But not one size fits all. It depends on the product and the manufacturing process.
” Further, Krishnamurthy points to the advantages of having complete visibility across a supply network, not just of inventory in warehouses, but in transit, too. All in all, you need to be able to pool inventory across channels to minimize investment. From a technology perspective, generative AI is a game-changer, because demand-sensing is a pretty lengthy process, and it’s not easy to plug into all the sources of data, he says.
“Today, with AI you can plug into all the different nodes in your network to get visibility into inventory. AI also provides the capability to immediately sense and flag supply chain disruptions before they affect the customer. These developments are important from a customer experience perspective,” Krishnamurthy says.
Krishnamurthy adds that AI helps with some of the knottier problems of customer service, such as accurate delivery times. Telemetry can show where trucks are real time, and AI models can predict potential fulfillment issues – to see the yellow flag before it becomes a red one. “We have active conversations with our customers that one of their biggest challenges is that their customer does not have visibility into when their order is going to be delivered.
They want to know what day and what time the delivery is coming into the DC. That’s not something new; you would think it would have been resolved a long time ago.” He says the issue has been that a supplier may have its top four or five carriers that offer great visibility, but then there’s a long “tail” of secondary carriers who in the past have not typically been able to offer that.
With the type of technology platform Cognizant can offer its customers, there’s the capability to plug into a carrier that only has three trucks, by installing simple GPS devices on the trucks which send data into the platform, where it is integrated by AI to produce useful information. The software will also identify if there’s a problem on the route, and automatically alert and reroute drivers. Lastly, AI can help with after-sales support, which Krishnamurthy says is often not included in most conversations about customer experience.
But, he says, it’s important to consider how you enhance the customer experience beyond the point of delivery. The customer may have questions after the delivery, about unpacking or installing an item, for example. Many of these questions can be automatically answered via chatbot and, if not, the system kicks it up to the next level of customer support, with a human on the other end.
“This is important, because most customers don’t want to wait a day or two for answers,” Karsthik says. Another place where AI is being leveraged in after-sales support is to send an alert when a product is due for a service. “That’s predictable via algorithm and predictive analysis, so you know when spare parts will be required,” says Krishnamurthy.
“You’re able to provide a single, seamless supply chain that includes after-sales support.” By integrating these advanced strategies and digital technologies, manufacturers can cultivate stronger customer relationships and drive long-term success in the B2B landscape. This approach not only enhances operational efficiency, but also fosters customer loyalty and satisfaction, both of which are key to sustainable growth in today’s dynamic business environment.
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