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eDelivery data focus: the future of big data & IoT, readers share their views


Earlier this week, we asked readers to share their views on the importance of data analytics, big data, and tech investment for the retail operations and logistics industry.
We’ve had a range of people contact us, expressing different views but broadly in agreement on the importance of data to the sector. There is a lot of data in retail, and the number of sources of data is always on the rise. From CRM systems, to email marketing stats, from sales information, to comments collated by contact centre personnel. Making sense of it all, and being able to use that data to form insights that will better equip your delivery network is far harder than acquiring that data in the first place.

Mark Thornton, marketing director at Maginus, thinks that when it comes to big data in particular, there are small differences to be made that will bear fruit, especially in the b2b delivery sector.

Mark Thornton, Maginus

Mark Thornton, Maginus

“I’m of the opinion that ‘big data’ principles do not have to be that ‘big’ to make a difference for retail operations and logistics companies. Business intelligence and data warehousing have been around for decades making the same promises. Now, with the advent of SaaS based products and cheap data storage in the cloud, these solutions are available to everyone – and can help businesses in the sector make better decisions and develop new ‘value add’ services.

“As an example, in retail software such as Clear Returns has proven the financial benefits in operations and logistics for the analysis and understanding of returns. The same analysis in B2B could give insights into individual merchants or tradesmen with particularly expensive return behaviour. It allows an agile business, with the right IT solutions, to alter the customer relationships; perhaps removing free delivery for those difficult customers.

“Furthermore, wholesalers with a close working relationship may reveal a manufacturer’s product regularly being returned because of a specific fault or because customers can’t get functionality to work. This may lead to changes in production, or improved documentation or video content. A win-win for the entire supply chain.

“These examples highlight how intelligent digital information can help pinpoint appropriate offline activity to continue driving retail operations and logistics businesses forward. Just a little bit of ‘big data’ can help shape so many decisions, showing it has a central role to play in the future success of the sector.”

Stuart Rivett, managing director of B2C Europe, worries that the term big data lacks substance and without some of the basics in place, it won’t be of much value anyway.

Stuart Rivett, B2C Europe (UK)

Stuart Rivett, B2C Europe

“Big Data is not just a descriptive term for us. Most businesses will claim to have Big Data in some form, however we feel that without having the right interpretations, analytics and processes in place, such data can be meaningless.

“Within logistics and operations, we are seeing some carriers collecting Big Data and transforming it into useful information that can be used to help improve the level of service to customers and end consumers. For example, for businesses that are working with multiple carriers, the analysis of individual carrier performance against national benchmarks can be extremely helpful.

“This data also helps to plan efficiently for peak periods. It allows businesses to accurately forecast volumes based on previous years, so helping to avoid issues and proactively putting procedures in place to ensure efficiency. For instance, by allocating additional resources where required during busy times such as Christmas and proactively managing capacity issues.”

Adrian Carr, senior vice president at database provider MarkLogic, warns that the volume of incoming data is only going to get worse, and that getting on top of it now might be your only option.

“Supply chain philosophy for years has been about aggregation and economies of scale. With the advent of big data and disruptive technologies that philosophy needs to be rewritten.

“These changes will be felt from the high street back to the producer. The high street will once again be populated by small shops with fresh produce, differentiating themselves with quality of product and service. Meantime homogeneous products will be delivered from depot or manufacturer directly to the consumers’ door.

“The amount of data to be crunched is increasing exponentially. For example The Internet of Things will have a huge impact on the retail supply chain in retail and will generate huge volumes of data. Whereas in the past the retailer has dominated the data landscape, being the hub of the web of suppliers and customers, this will change to the supplier becoming more of a facilitator between the manufacturer and consumer. The difference is that the supplier will become a brand.

Big Data has huge implications for data platforms. The ability to scale tremendously to cope with high volumes at speed requires a commodity architecture where adding extra nodes adds more capacity. While much of the data will be raw transactional information, there will also be consumer data, requiring security features.

Any technology will also need other enterprise features such as resilience and consistency across the platform. Perhaps the most challenging aspect for the data platform will be the need to integrate with a vast array of systems and devices, accommodating a near infinite set of formats. Standardisation may emerge one day but in the meantime a ‘universal plug’ or more specifically, a schema-agnostic data integration tool is a pre-requisite to avoid endless data modelling and transformation.”

Patrick Gallagher, CEO of On the dot, gives an interesting example of how analysing data starts to lead the way to better resource allocation and planning.

Patrick Gallagher, CitySprint

Patrick Gallagher, On the dot

”Using customer data – big and small – to understand purchase context is vital for getting convenient delivery right. 2016 On the dot research found that 10am and 6pm are the most popular times in the UK for specified hour delivery. But these times become less important for items that customers need more urgently or for a specific purpose. This is when delivery at any time, as long as it is speedy, is most convenient.

”With purchase context playing such an important role in what convenience means for today’s consumer, retailers cannot afford to second guess customer needs. Instead, they should leverage all data from customer journeys to understand why and when customers require convenient delivery and make predictions for future purchases.

“Big data in particular can help retailers track trends that apply to their entire customer base; but even simple cues, such as ticking the gift wrapping option, can tell retailers a lot about a purchase and the most suitable delivery options to offer.”

Vicky Brock, CEO of Clear Returns, points out that big data is a term that gets thrown around a lot, but understood a good deal less.

Vicky Brock, Clear Returns

Vicky Brock, Clear Returns

“It is important to note first that the term ‘big data’ is often misused and misunderstood within the industry. While it’s essential that retailers and supply chains use the data that is available to them, the analogy that describes data as ‘crude oil’ in its raw form – which only becomes truly valuable once processed – couldn’t be more accurate.

“Data enables retailers to observe, review and learn from current and past trends while obtaining a deeper understanding of the specific area they are analysing. It can help retail operations and logistics by exposing current stock management efficiencies and return rates, the reason why these goods are sent back, and operational records, such as whether the item was correctly processed and resold.

“Many retailers struggle to cope logistically with returns, as much of their focus is traditionally set on product promotion and selling strategy. However, by collating and analysing data on returns, retailers will begin to understand the psychology behind them, enabling them to adjust both their marketing and operational strategy to ensure they’re not only reducing the quantity of goods sent back, but are logistically prepared for those that are returned.

“Big Data can shed light on why items are being returned, how customers are choosing to send goods back, and how loyal / valuable the ‘returner’ is.”

Add your voice to the conversation … can data unlock hidden value in delivery networks, what’s your take on big data, is it hype or hope? To share your views you can leave a comment below or contact us via email.

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