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Every day, companies collect massive amounts of data from any number of sources, including social media and Internet of Things-enabled devices embedded with electronics, software, sensors and network connectivity that let these objects gather and share data. And some are looking to supply chain analytics to make sense of all this data so they can cut costs, operate more efficiently and offer better customer service.
Take The Bouqs Company, a cut-to-order, farm-to-table, eco-friendly flower retailer delivering straight from farms -- one on a volcano in South America. The company knows how to save money at each stop along the supply chain from farm to flower recipient, said John Tabis, founder and CEO of the firm, based in Venice Beach, Calif.
Typically, flowers go from farm to wholesale, wholesale to retail and retail to consumer, wasting about 17 days of the lifespan of a commodity that only lasts 21 days. The Bouqs is aiming to change the flower industry for the better with farm-to-door flowers that are only cut once a customer places an order and arrive on day four rather than day 17, Tabis said.
"When you place an order, we look at what's available from the farms and what the projected production is on a per-acre-by-flower level," he said.
Supply chain analytics allows The Bouqs to constantly analyze the data the farms input into its systems to determine what's available for sale.
"Where analytics comes into play is we're using historical sales to estimate what we think is going to sell in terms of volume of any given type of flower in any given month so we can ensure that our farm network can satisfy that demand," Tabis said.
Supply chain analytics boosted by data explosion
There is a lot more data available for supply chain analytics compared to a couple years ago, according to ShiSh Shridhar, retail industry solutions director at Microsoft.
Internet of Things (IoT) is just one source. There's a lot of real-time locational data available from sensors and radio frequency identification (RFID) tags -- data that software can analyze and act on. The other thing accelerating what companies can do with supply chain analytics is the availability of public data, Shridhar said.
Companies can put an additional layer on top of their historical data: weather, demographic, economic and social media data that can provide insight into product demand. "Now you don't have to just rely on historic data to predict demand, to better understand behavioral patterns and how certain geographies work," he said.
Understanding the current location of goods as they're being shipped no matter what mode -- rail, truck, ocean -- is key to optimizing supply chains, said Jim Hayden, vice president of solutions at Savi, which makes sensor and analytics technology.
"From an analytics perspective, we're building these predictive models on arrival times based on as much historical information as we can gather as well as third-party data sources such as traffic and weather," Hayden said. "And we're building machine learning-based models to help predict estimated times of arrival."
For example, if a manufacturer determines that a supplier is going to be significantly late, it can make a decision earlier to stop the production line and not wait around for the late shipment.
Companies also use supply chain analytics to figure out how the lateness of one shipment will affect other shipments downstream and in real time, said Mark Palmer, senior vice president of engineering at Tibco Software.
"Based on the predictive signals you find in Spotfire [Tibco's analytics software], you could say 'Let's hold up a particular shipment or send an alert to an operator to manually figure out what's going on," he said. "There's a tie between Spotfire for finding patterns on connected vehicles that can feed into the way you execute against the actual real-time data stream."
Bullwhip effect minimized with supply chain analytics
In supply chain management, the goal is to avoid the so-called bullwhip effect, which causes businesses down the supply chain to either undersupply or over supply the actual demand, said Justin Bateh, professor of business at Florida State College at Jacksonville.
It occurs because demand is based on companies' demand forecasts rather than the actual demand from customers.
"This can happen if a company is running a promotion and is placing a lot of orders [for a particular product] because of the promotion, but the manufacturer assumes demand has increased [in general] and starts producing more," Bateh said. "Because the customer and the manufacturer are not in sync with each other, there is a distortion in demand."
This is where working together and supply chain analytics come into play.
By linking up order, point of sale and inventory systems, everyone in the supply chain can see the data in real time and analyze it to gain insight into what is actually selling, minimizing the bullwhip effect, he said.
StockPKG, a one-stop shop for business supplies in Dana Point, Calif., uses analytics to improve everything, including its supply chain.
"We use analytics to track how often we get accurate shipping information from our carriers such as UPS and FedEx," said Blake Stoudt, the company's marketing manager. "We track if the deliveries get to their destinations at the times the carriers said they did."
StockPKG uses data from the accuracy reports provided by carriers. First, the company logs that data into its customer relationship management system, then checks it against information that customers provide via an online form.
"If we discovered that packages to one area were always being delivered late, we would call our rep at the carrier and say we would need to address it," Stoudt said.
Jack Allen, senior director of logistics and manufacturing solutions at Cisco Systems, said that analyzing where trucks go and how long they take to get there also pays pretty big dividends for companies like UPS.
In fact, a couple years ago, UPS acknowledged it collects and analyzes data from sensors on each of its trucks to record to the second everything a driver does, including loading packages in the morning and backing up too much, to figure out how to do things more efficiently.
Watching how vehicles move pays big dividends, Allen said. "So we're wiring up in our proving ground wireless infrastructure to be able to do location-based data and trying to track, for example, if people are too far to pick parts, and if we can move those parts much closer."
Allen said supply chain analytics will enable Cisco to glean insight from the rich data gathered by sensors on forklifts and wearables to help it optimize the warehouse pretty substantially. The technology can then be used to help Cisco's customers, he said.
Companies can also use analytics to analyze sentiment data from social media to understand what is going to be successful as a new product, said Simon Ellis, an analyst at IDC.
"This helps the manufacturer's supply chain because you don't waste time and resources on new products that won't be successful," he said.
Chinese computer maker Lenovo is doing just that. When Lenovo releases a new product, social media channels immediately start to buzz with what users love and hate about it, said Mohammed Chaara, director of customer insights and advanced analytics at Lenovo.
"As a manufacturer that ships a device every four seconds, we knew this timely feedback could help us make better business decisions," he said. "But we didn't have a way to capture and analyze the data efficiently and in time to affect decisions about product design, etc. We knew if we could identify trends indicated through social media sooner, we would be able to address issues sooner, too."
So Lenovo worked with analytics vendor SAS to create a system to track, analyze and quickly respond to social chatter.
"That speed around a product launch equals millions of dollars in benefits to a customer the size of Lenovo," Chaara said.
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