glassbeam logoBy Puneet Pandit
Founder and CEO, Glassbeam, Inc.
 
IoT machine data analytics has been generating actionable information from huge streams of information coming from hundreds and often thousands of sources within a host of vertical market devices over the past few years.  Now, innovative supply chain managers are leveraging real time analysis to improve customer service, reduce the cost of that service, improve inventory control, and even identify new services with a potential to increase revenue.    These IoT solutions are not expensive, yet can save thousands and even millions of dollars every year.
 
Companies that stock, sell, and service physical products have been seeking ways to improve operational efficiencies for decades. In many organizations, there have been ample opportunities for improvements in all facets of the business, including order management, customer support, service fulfillment, returns/replacements, shipping, and logistics. IoT analytics offers the ability to enhance all of these areas, faster and with much more accuracy because the information is coming from the field instantly.
 
This new generation of IoT analytics collects, distills, analyzes, and presents massive amounts of operational data in easy-to-digest formats. These automated solutions help the supply chain in three ways:
 
1. Proactive support: Applying rules to incoming data and taking automatic proactive action, such as opening up a customer case, alerting a support team to take preventive action, or dispatching a part (or more sometimes more important, determining that a part doesn't need to be dispatched to solve the problem).
2. Predictive maintenance: Uncovering failure rates before failures happen.  Essentially, before an incident happens, customer service or field ops teams become aware that an incident is "about to happen" and can address a problem.
3. Prescriptive maintenance: Before an incident happens, machine data analytics can provide information to remedy engineering teams to help prevent the incident through an interface with a knowledge base.  And the analytics can provide tips to avoid a potential problem as well.
 
In order management, IoT technology analyzes order trends and reveals inefficiencies in the account start up process and management of orders.  Results of this analysis can help product companies reduce broken orders, and lead to improved practices for account activation and management.
 
Once the product arrives and is installed at the customer site, IoT analytics can let operations managers know when the machine the product is a part of may need maintenance or repair; can predict when the machine may need attention; and can often identify the product or products causing the need for maintenance or repair and recommend remediation activities.
When it comes to service level agreements (SLAs) or similar performance guidelines IoT analytics can have a significant impact.  Analysis can identify real or potential issues in improving management of deliveries in near real time, optimizing inventory practices and rapidly addressing service events.
 
Of course, despite best efforts, a small percentage of defective products will make it through the supply chain and on to customers.  IoT analysis can minimize the impact of these products in two ways. First, analytics can help product company management identify which parts or processes in the manufacture of the product are creating the defect. Next, IoT analytics can optimize efficiencies in the repair channel so that the customer is minimally impacted.
 
In shipping products to the customers, IoT analytics can also identify bottlenecks in the delivery, invoicing, part replenishment and customer helpdesk functions. Managers can then streamline these functions and enable them to contribute to reducing costs and improving customer loyalty.
 
No matter what industry you supply and service, the use of machine data analysis can identify new opportunities to improve all areas of the supply chain and enable you to streamline processes, improve customer satisfaction, reduce costs and enhance the bottom line.  As an innovative manager eager to optimize all aspects of your businesses IoT analytics is worth looking into.  You can bet your competition is.
 
About the author:
Puneet Pandit is the founder and CEO of Glassbeam, a provider of machine data analytics software. Prior to Glassbeam, he was founder and CEO of Orchesys, a professional services firm focused on enterprise storage solutions. Glassbeam was incubated inside Orchesys and launched in 2009. Prior to Orchesys, Puneet led the Database and Business Applications Solutions Group at NetApp. He also worked at Ernst & Young strategic advisory services and Tata Unisys as a management consultant. Puneet holds an MBA from University of Chicago and graduated with Electrical Engineering degree from Punjab University.

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