Everyone knows that the retail industry is being transformed by digital, analytics and big data. Winning requires continual data-driven experimentation and transformation.
Shortened time from idea-to-app is a constant challenge.
Evidence of this “digital disruption” by category are mounting every day. Wal-Mart closes 269 stores as it retools portfolio to compete with online natives like Amazon.com. Macy’s said that it will shutter over 36 stores as store traffic declines faster than expected, and Finish Line said that it would close 150 stores by 2020. Gap, J.Crew, American Apparel, Sears and Kmart are all facing similar headwinds.
Starbucks CEO Howard Schultz laid out his thoughts on the future prospects for retail business, “three years ago we began to envision that there would be a seismic change in consumer behavior, and that seismic change was due in large part to e-commerce, omni-channel and smartphone shopping.”
It’s fascinating to watch retailers trying to shift tech/platform strategies to deal with digital disintermediation, showrooming, asset-light models, physical-to-digital channel integration, mobile shoppers, same-day delivery/fulfillment, programmatic targeting, online native models and now the new buzz.. virtual and augmented reality.
Several retailers have invested in Big Data and Hadoop platforms to mine massive volumes of structured transactional, operational data and unstructured data—web logs, clickstream data, geo-location data, social interactions and sensor data.
While most retailers understand the mega-shift and seems to know what to do….they are unable to execute consistently or effectively. A talent gap in many cases. A platform gap in others. Others are hindered by legacy IT systems or don’t have the necessary technology capabilities in place.
I think the digital induced pain is going to get worse in 2016 and 2017. Consumers will continue to diversify their retail activity across channels in search of the best value, forcing retailers to spread out their digital investments. This puts additional stress on execution and leadership.
In this summer’s blockbuster movie “Edge of Tomorrow,” a PR executive played by Tom Cruise goes through innumerable time loops to become a soldier by being reborn every time he is killed. In the context of software startups, successful products are built through repeated testing and improvement. Those that can do the most iterations without dying become the needle-movers.
The evolving Internet of Things (IoT) ecosystem presents opportunities for startups that can create sustainable solutions. Further to our article, “Internet of Things Needle-Mover Opportunities,” we looked at companies that will form the basic foundation of technologies that address the following five IoT challenges:
- Privacy and security
- The power barrier
- Data analytics and management
- Interoperability and integration
The automated vote-counting machine was designed by Thomas Edison in 1869 to replace roll call voting in the U.S. Congress and was never used. The motor scooter was designed in post-war Italy to be a motorcycle for women and became a revolutionary transport mechanism for a larger population. The Java programing language was originally designed in the 1990s for use by set-top boxes. And eBay was created to sell Pez dispensers. History has many examples of how original use case definitions became irrelevant in the face of market economics. Like any other new technology, the Internet of Things (IoT) will create an ecosystem with its share of winners, losers, survivors — and needle movers.
Today, use cases abound on how the IoT’s connected devices can create economic value. Some analysts talk about white spaces of solutions that span industrial, commercial and consumer applications. Others talk about fundamental challenges in delivering on the promise of IoT. While white space use cases will have hits and misses, IOT-enabling technologies represent a much larger opportunity for innovative value creation.
The “real meat and potatoes” use cases behind big data actual adoption might be around B2B machine data management and Industrial analytics enabled by wireless, battery-free sensor platforms.
While social, consumer, retail and mobile big data get a lot of PR, the big data business cases around industrial machine data analytics or “things that spin” actually make economic sense. These projects tend to show tangible Return on Investment (ROI).
The concept of Internet-connected machines that collect telemetry data and communicate, often called the “Internet of Things or M2M” has been marketed for several years:
– I.B.M. has its “Smarter Planet” initiative
– Cisco has its “Internet of Everything” initiative
– GE has its “Industrial Internet” initiative.
– Salesforce.com has its “Internet of Customers” theme
To compete with GE….Hitachi, United Technologies, Siemens, Bosch, Schneider Electric, Phillips and other industrial giants are all getting on the band-wagon as the vision of M2M is now viable with advances in microelectronics, wireless communications, and microfabricated (MEMS) sensing enabling platforms of rapidly diminishing size.
The Bosch Group has embarked on a series of initiatives across business units that make use of data and analytics to provide so-called intelligent customer offerings. These include intelligent fleet management, intelligent vehicle-charging infrastructures, intelligent energy management, intelligent security video analysis, and many more. To identify and develop these innovative services, Bosch created a Software Innovations group that focuses heavily on big data, analytics, and the “Internet of Things.”
Similarly, the Schneider Electric focuses primarily on energy management, including energy optimization, smart-grid management, and building automation. Its Advanced Distribution Management System, for example, handles energy distribution in utility companies. ADMS monitors and controls network devices, manages service outages, and dispatches crews. It gives utilities the ability to integrate millions of data points on network performance and lets engineers use analytics to monitor the network.
Industrial Internet – making smart use of sensors, networked machines and data analytics – is the big vision, but the business driver is in no unplanned downtime for customers.