DHL: four key trends shaping the future of e-commerce
E-commerce was form...
E-commerce was formerly unique to the retail sector and B2C market, however, it has since become an important component in B2B transactions. Now used across all sectors, it is thought that business e-commerce in the US could reach $1.2trn by 2021, according to research firm Forrester.
1. The rise of ‘social commerce’ and virtual marketplaces
It has been discovered that consumers are transitioning away from purchasing online from corporate websites. Forrester’s research found that 67% of B2C online sales will take place on virtual marketplaces by 2022. “Until recently, it was mostly brands, distributors and retailers who would sell us the things that we consume online,” commented Nabil Malouli, VP, Global E-Commerce at DHL. “Now, however, it’s not just well-known marketplaces such as Amazon, Alibaba, eBay and Etsy who are extremely powerful, it’s also some of the new players enabling social commerce - the Instagrams and Pinterests of this world - to allow smaller businesses to sell to the world.”
2. Innovative approaches will be key to tackling labor shortages
With the significant increase in e-commerce contributing to a shortage of labour in the logistics space, peak days consist of around 30% of the year’s volume for some retailers, it’s important that orders are fulfilled efficiently otherwise valuable customer sentiment and returning customers could be lost. “DHL uses automation in many instances because it’s the only way of meeting the required service level,” added Malouli. “Large retailers can process up to 500,000 orders in a single day during peak time. Such volumes can’t be handled manually.”
3. Growth in e-commerce means growth in returns
With a rise in e-commerce, it also means an increase in returned goods by nature. The need for reverse logistics is a major factor in warehouse space being leased and is having a significant effect on warehousing in the US. It is thought that the need to handle returned good consists of around 700mn sq. ft of warehouse space in the US alone. “When consumers buy an item in a store, the average return rate of store item purchases is less than 10%,” said Spencer Levy, Americas Head of Research and Senior Economic Advisor for CBRE. “With internet purchases, the return rate can be more than 30%, so there’s an enormous difference.”
4. The convergence of online and offline
There has already been the beginning of convergence of online and offline with transactions such as Amazon’s $14bn acquisition of physical grocery chain Whole Foods. China’s Alibaba has also announced its new retail strategy which has seen it open bricks and mortar grocery stores and pop up shops, in addition to partnering with 600,000 smaller stores. “Some companies are doing it very well,” said Malouli. “Fast fashion retailer Zara, for example, has created an omnichannel experience at its new London concept store. But other companies which started out as mainly distributors of brands and that have managed online and offline as different businesses, with different technology backbones, have a hard time managing the experience. It’s convergence that is key.”
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5 Minutes With: Jim Bureau, CEO Jaggaer
What is data analytics, and why is it important for organisations to utilise?
Data analytics is the process of collecting, cleansing, transforming and analysing an organisation’s information to identify trends and extract meaningful insights to solve problems.
The main benefit for procurement teams that adopt analytics is that they’re equipped to make faster, more proactive and effective decisions. Spend analysis and other advanced statistical analyses eliminate the guesswork and reactivity common with spreadsheets and other manual approaches and drive greater efficiency and value.
As procurement continues to play a central role in organisational success, adopting analytics is critical for improving operations, meeting and achieving key performance indicators, reducing staff burnout, gaining valuable market intelligence and protecting the bottom line.
How can organisations use procurement analytics to benefit their operations?
Teams can leverage data analytics to tangibly improve performance across all procurement activities - identifying new savings opportunities, getting a consolidated view of spend, understanding the right time for contract re-negotiations, and which suppliers to tap when prioritising and segmenting suppliers, assessing and addressing supply chain risk and more.
Procurement can ultimately create a more comprehensive sourcing process that invites more suppliers to the table and gets even more granular about cost drivers and other criteria.
"The main benefit for procurement teams that adopt analytics is that they’re equipped to make faster, more proactive and effective decisions"
Procurement analytics can provide critical insight for spend management, category management, supplier contracts and negotiations, strategic sourcing, spend forecasting and more. Unilever, for example, used actionable insight from spend analysis to optimise spending, sourcing, and contract negotiations for an especially unpredictable industry such as transport and logistics.
Whether a team needs to figure out ways to retain cash, further diversify its supply base, or deliver value on sustainability, innovation or diversity initiatives, analytics can help procurement deliver on organisational needs.
How is data analytics used in supply chain and procurement?
Data analytics encompasses descriptive, diagnostic, predictive and prescriptive data.
Descriptive shows what’s happened in the past, while diagnostic analytics surface answers to ‘why’ those previous events happened.
This clear view into procurement operations and trends lays the groundwork for predictive analytics, which forecasts future events, and prescriptive analytics, which recommends the best actions for teams to take based on those predictions.
Teams can leverage all four types of analytics to gain visibility across the supply chain and identify optimisation and value generating opportunities.
Take on-time delivery (OTD) as an example. Predictive analytics are identifying the probability of whether an order will be delivered on time even before its placed, based on previous events. Combined with recommendation engines that suggest improvement actions, the analytics enable teams to proactively mitigate risk of late deliveries, such as through spreading an order over a second or third source of supply.
Advanced analytics is a research and development focus for JAGGAER, and we expect procurement’s ability to leverage AI to become even stronger and more impactful.