Do your customers engage with multiple touch points in your business? Or are you simply just looking to decrease the complexity of your supply chain? Transforming your supply chain operating model shouldn’t be done lightly, and although there are a variety of motivations to improve supply chain performance, you should try to attain clear and defined goals and objectives.
Overly complicated processes and organisations may find that customers are interacting with different departments that uphold different standards of performance. And similarly, responding to market needs means you need to gather, analyse and prioritise customers’ expectations to ensure your supply chain can accommodate them. To do this you need data. But it’s difficult to attain and make proper use of data if your supply chain operates in silos.
Achieving a seamless, end-to-end information supply chain can help businesses improve performance and respond to market needs effectively. In this post we data as the substrate for your supply chain so you can start delivering the experiences your customers expect.
Why ineffective collaboration is hurting your customer experience
Do you truly understand what your customers expectations are? And are your products delivering on that expectation? In this new climate of instant gratification, you must looks beyond a single product or services that you’re delivering, and consider the first, to the very last, touch points your customers are interacting with.
Customers today have a certain expectation for a service basis. If you have a premium product, and the customer is paying more for that product, customers expect more when they are paying more. This couldn’t be more pertinent today, because if a customer isn’t paying for, say express international shipping, they often will rationalise purchasing a few more items to get shipping for free.
If you’re an eCommerce business, it’s worth noting that many customers today don’t see shipping for online purchases as an extra service. In fact, giving them the choice of paying extra for express shipping, or being able to select the free shipping option can enhance your customer service reputation automatically.
Our everyday interactions with technology have changed the way customers interact with businesses. The expect more personalisation, the more payment options, self-service, social means of contact, they expect you listen closely and respond quickly to their queries, and most of all, they want one point of contact that can make decisions on the fly.
So how can businesses achieve this? Let’s look into 3 different ways big data can deliver a better customer experience
3 ways to strategically manage your supply chain through data
“Supply chain and logistics automation is neither easy nor cheap, but it is the biggest opportunity for most companies to significantly reduce their cost and improve their performance.,” wrote H. Donald Ratliff, Ph.D., executive director of the Supply Chain and Logistics Institute.
Meeting customers’ needs isn’t cheap. But according to Donald, “there is an opportunity to reduce cost by 10% to 40% by making better decisions.”
Data can help ensure your business can create a flexible ecosystems with as little operational inefficiencies as possible. The below 3 data strategies should help you overcome the above challenges facing many supply chain manager today.
1. Don’t wait. Predict what your customers want
Did you know that 90% of customers would not return to a business they feel dissatisfied with or if the company has failed to meet their expectations? So why not predict what they want before they even tell you?
Amazon recently patented their anticipatory shipping algorithm so they can ship products that are regularly purchased by customers before they even order them. Think about, Mary orders toilet paper every first Tuesday of the month. Amazon’s algorithm-based system can detect and predict this to make Mary’s life a little easier.
Not all business have this capability though, but there are some smaller measure you can take to predict what your customers are after. Offer the right product, to the right person at the right time and place. This means you need to collect data on how your customers are interacting with your brand, ensure your systems are connected and be sure you have stock, and then predictively offer a product that fits their needs and purposes.
Taking this away from the customer-centric view, predictive analytics also help businesses integrate demand forecasting and optimise business planning and supplier collaboration. Interestingly enough, these benefits will also make your customer happy buyers.
2. Accelerate supply chain processes for greater efficiencies
“Embedding big data analytics in operations leads to a 4.25x improvement in order-to-cycle delivery times, and a 2.6x improvement in supply chain efficiency of 10% or greater” writes Louis Columbus from Forbes.
Sometimes pictures are better than words. Take a look at the graph below to compare businesses that have embedded big data and analytics on a day-to-day basis when compared to those who use it on an ad hoc basis.
3. Improve reaction time for a more agile supply chain
Meeting customers fulfilment objectives through shipping options was covered above, but we didn’t mention that quickly and flexibly meeting customers needs was rated as the second most important driver of competitive advantage. So it’s not to be taken lightly (SCM World Chief Supply Chain Officer Report 2014).
Big data can improve your business’ reaction time should any supply chain issues arise, but on top of that, big data can help detect problems even before they arise.
There are always certain elements you can control and elements you can’t control within your supply chain. For example, you can’t control if there will be a hurricane next week that might prevent order fulfilment. However, you can improve your supply chain traceability performance and reduces the many hours of manual labour required to assess and integrate databases that manage these types of events.
According the Accenture, big data and analytics can improve supply chain efficiency by 10% or even greater. That means you’ll be able to spend more time focusing on fulfilling your customer expectations.
We hope this post has helped you to think differently about big data in your supply chain, and maybe it will even start some conversations. Have you got any comments on this post? Let us know your thoughts.