How To Pilot Emerging Tech, Like Social Media, Wearables, IoT, AI, Analytics, Crypto & Blockchain
Here’s the list of technologies everyone should be tracking -- and piloting:
- Cloud Computing
- Location-Based Services
- Augmented, Virtual & Mixed Reality
- Social Media Analytics
- Wearable Technology
- The Internet-of-Things
- AI/Machine Learning
- Augmented Analytics
- Cloud Computing
- Location-Based Services
- Augmented, Virtual & Mixed Reality
The focus here is on all the rest of the technologies and the process of piloting these and other emerging technologies.
Five simple steps:
- Describe the Emerging Technology w/Reference to Business Impact
- Target the Potential Impact at Specific Business Models & Processes
- Identify Sponsors (w/Resources) to Champion Pilot Demonstrations
- Develop Pilot Project Plans (with Empirical Impact Metrics)
Social Media Analytics
Social media analytics “is the process of gathering data from stakeholder conversations on digital media and processing into structured insights leading to more information-driven business decisions and increased customer centrality for brands and businesses … there are three main steps in analyzing social media: data identification, data analysis, and information interpretation.” Social media analytics impacts a variety of products and services including customer satisfaction, brand management, innovation, competitor analyses and customer acquisition, among any process where market, competitor and customer insights might be leveraged. Impact can be measured in a series of pilots, but – as always – pilots need funding and sponsorship -- and impact metrics displayed in dashboards that make it easy to see the location and extent of impact.
“Wearable technology is a blanket term for electronics that can be worn on the body, either as an accessory or as part of material used in clothing. There are many types of wearable technology but some of the most popular devices are activity trackers and smartwatches. One of the major features of wearable technology is its ability to connect to the internet, enabling data to be exchanged between a network and the device. This ability to both send and receive data has pushed wearable technology to the forefront of the Internet of Things (IoT).”
Wearable technology impact can be defined in at least two major ways. Some companies (1) create wearable technology and some (2) apply wearable technology to their products and services in, for example, clothing, smart watches, trackers, shoes and other external or implanted wearables which can improve, extend, modify to replace functionality of existing products and services. Hypotheses (that define the pilot project plan) should be developed that will measure the impact of wearable technologies likely to be cost-effective, competitive and deployable across these two impact areas.
The Internet of Things (IoT)
“The Internet of Things (IoT) refers to a network comprised of physical objects capable of gathering and sharing electronic information. The Internet of Things includes a wide variety of ‘smart’ devices, from industrial machines that transmit data about the production process to sensors that track information about the human body. Often, these devices use internet protocol (IP), the same protocol that identifies computers over the world wide web and allows them to communicate with one another. The goal behind the internet of things is to have devices that self-report in real time, improving efficiency and bringing important information to the surface more quickly than a system depending on human intervention.”
IoT is designed to extract data from a process, a device or a human to make a process 'smart,' or solve some specific problem. The potential impact should be measured against a set of specific smart objectives. IoT will enable smart buildings, smart cities, smart networks, smart clothing and just about everything and process imaginable. IoT permits quantitative-empirical measures of effectiveness that can be estimated and validated.
Artificial Intelligence/Machine Learning
“Artificial intelligence (AI) is a term for simulated intelligence in machines … the ideal characteristic of artificial intelligence is its ability to rationalize and take actions that have the best chance of achieving a specific goal ... based around the idea that human intelligence can be defined in such exact terms that a machine can mimic it … (applied to) learning, reasoning and perception … (through) a cross-disciplinary approach based in mathematics, computer science, linguistics, psychology and more.” “Machine learning is the concept that a computer program can learn and adapt to new data without human interference. Machine learning is a field of artificial intelligence (AI) that keeps a computer’s built-in algorithms current … various sectors of the economy are dealing with huge amounts of data available in different formats from disparate sources … the enormous amount of data, known as big data, is becoming easily available and accessible due to the progressive use of technology … when new or additional data becomes available, the algorithm automatically adjusts the parameters to check for a pattern change, if any.”
AI is unique because it learns and self-replicates. There’s a bona fide arms race underway among investors in AI. The range of applications is staggering, including all of the vertical industries and just about every business function and process that supports them. AI will profoundly impact healthcare, transportation, accounting, finance, manufacturing, customer service, aviation, education, sales, marketing, law, entertainment, media, security, negotiation, war and peace. The impact of AI/ML can be measured in a series of pilots designed to widen and deepen insight into its role in all business models and processes. As always, pilots need funding and sponsorship.
“Augmented Analytics automates data insight by utilizing machine learning and natural language processing to automate data preparation and enable data sharing. This advanced use, manipulation and presentation of data simplifies data to present clear results and provides access to sophisticated tools so business users can make day-to-day decisions with confidence. Users can go beyond opinion and bias to get real insight and act on data quickly and accurately.”
Augmented analytics builds upon existing investments in analytics which fall into one of four categories: description, explanation, prediction and prescription. The impact should be focused on these areas. It must be assumed that companies are already piloting analytics methods, tools and techniques in one or more of the primary applications areas (description, explanation, prediction or prescription). As always, pilots need funding and sponsorship. AI/ML and augmented analytics are closely related. Augmented analytics is a “horizontal” application area for AI/ML, so pilots in one area can impact the other.
According to Francois Zaninotto, “a blockchain is a ledger of facts, replicated across several computers assembled in a peer-to-peer network. Facts can be anything from monetary transactions to content signature. Members of the network are anonymous individuals called nodes. All communication inside the network takes advantage of cryptography to securely identify the sender and the receiver. When a node wants to add a fact to the ledger, a consensus forms in the network to determine where this fact should appear in the ledger; this consensus is called a block… a blockchain allows to securely share and/or process data between multiple parties over a network of non-trusted peers. Data can be anything, but most interesting uses concern information that currently requires a trusted third-party to exchange.”
Some of the more prominent application areas include financial services (such as asset management, cross-border payments, insurance claims processing and smart contracts). Blockchains can be threatening because by their nature they disrupt transaction architectures. They do this by disintermediating trusted third parties – like banks. Consequently, pilot project sponsors may be somewhat more difficult to find than sponsors for other emerging technologies.
James Royal explains cryptocurrency this way: “Cryptocurrency is a form of payment that can be exchanged online for goods and services … cryptocurrencies work using a technology called blockchain … a decentralized technology spread across many computers that manages and records transactions. Part of the appeal of this technology is its security … supporters see cryptocurrencies such as bitcoin as the currency of the future and are racing to buy them now before they become more widespread and presumably more valuable … some supporters like the fact that cryptocurrency removes central banks from managing the money supply, since over time these banks tend to reduce the value of money via inflation … other supporters like the technology behind cryptocurrencies, the blockchain, because it’s a decentralized processing and recording system and can be more secure than traditional payment systems … still others like the anonymity of the blockchain network, which allows for transactions outside government surveillance, including criminal activities.”
Pilots here are challenging since they might well threaten existing transaction processes. Alternative currencies threaten lots of vested financial interests. Pilots therefore need special sponsorship. An impact may not be what’s expected or desired.
There you have it: a list and a simple methodology. The key is to understand where the technologies can impact your business processes, products and services. This should be a continuous process, not something you address at the end of the year or every other quarter. The lists will change and your requirements will change. Rest assured your competition will be piloting these and other emerging technologies. If you lose this battle, you may lose the war.