This post explores some key innovations and technologies that are worthy of consideration for strategy planning in 2017 and beyond. Whilst each of the technology innovations are at different stages of maturity, hype and utilisation in the market, each should be considered for their potential uses and applicability as part of blue-sky innovation and strategic planning processes.
Artificial Intelligence and Machine Learning
Artificial Intelligence and machine learning include systems that appear to learn, understand, predict and operate with minimal (or no) human guidance. These characteristics make machines appear intelligent. Smart machines intelligent applications can change their future behaviour through learning. Real world examples include robots, autonomous vehicles, drones and virtual personal assistants, intelligent sensors, smart appliances and smart tools (such as a digital stethoscope).
The New “Realities” – Virtual and Augmented
Virtual reality (VR) is essentially technology that generates a virtual environment, and simulates a user’s physical presence in this environment through interaction. The virtual environment is separate from the real-world environment, and headwear is typically used to shut-out the immediate surroundings from the virtual world. In a work environment VR can be very beneficial for training, where staff can develop skills in the virtual world without the real-world consequences of failing.
Augmented reality (AR) overlays virtual objects with the environment around you. Unlike virtual reality, which creates a totally artificial environment, augmented reality uses the existing environment and overlays new information on top of it. The most well-known real-world example is Pokomon Go. Other examples include the Topshop AR dressing rooms which allows shoppers to virtually try on new clothes. There is also the Shisedio makeup mirror, the IKEA AR catalogue (to visualise how various furniture would look inside your home) and the IBM shopping app, which provides personalised information whilst browsing the shelves.
Mobile Wallet
The use of mobile wallets is continuing to go mainstream, and fully integrated mobile wallets are starting to become a reality. Mobile wallets store payment credentials to enable users to authenticate themselves and/or make transactions from a mobile device. The credentials can be payment-related, such as a bank card, bank account or prepaid card, or non-payment-related, such as a loyalty card or mileage card. There are also closed wallets that allow use at specific merchants and open wallets that allow use at many other merchants. Businesses, retailers and organisations need to embrace this change, and identify the opportunities and risks of the technology.
Natural Language Question Answering
Natural-language question answering (NLQA) technology is a type of natural-language processing technology, composed of applications that provide users with a means of asking a question in plain language. A computer or service can answer it meaningfully, while maintaining the flow of interaction.
Unlike information retrieval systems such as search engines, NLQA aims to supply users with “just the right information” instead of merely providing a list of hits. NLQA technology is improving at a rapid pace. Current day examples include SIRI, Cortana and GoogleNow, however they are more like voice assistants and text analysers than true NLQA systems. Future uses in business include the use of NLQA in answering customer queries, contact centre applications and staff training.
Analytics
Analytics comes in many variants. Some examples are predictive, prescriptive, real-time, graph, personal and embedded analytics. It is no secret that the use of analytics and business intelligence in helping make and shape business decisions is critical for all organisations. Analytics can be used to transition organisations from a reactive to a proactive mode of operations and must be considered a core enabler of strategic and operational development.
Geospatial and location intelligence
Geospatial and location intelligence (GLI) includes applications, infrastructure and tools that enable access to, and utilisation of, geospatial and location data of people, things and information for location-referenced information analysis.
It is estimated that 80% of all business data contains a location component. It is therefore critical to understand how location affects business. Properly analysing location can provide insights that support and improve decision making in virtually anything, including marketing and supply chain logistics and operations. Location intelligence involves layering multiple data sets spatially and/or chronologically, for easy reference on a map.
Location intelligence complements business intelligence – where business intelligence may find one-dimensional relationships between customer demographics or store and warehouse locations, location intelligence enables much deeper dives into the relationships between geography and customer data.
Blockchain
Blockchain is a type of distributed ledger technology where transactions are sequentially grouped into blocks. Blockchain is used to track the ownership of assets without the need for a central authority, which speeds up transactions and cuts costs whilst lowering the chance of fraud. Blockchain is widely known as the technology that underpins the digital currency bitcoin. Whilst blockchain is still a relatively new and experimental technology, the ecosystem is growing rapidly and includes start-ups to major technology vendors.
Blockchain comes with cautions however. Considerations include potential lack of transparency, limitations concerning consumption of resources, operational risk from unintended centralisation of resources; and lack of alignment to existing legal and accounting frameworks. There are also potential adoption challenges, including the lack of standards, robust platforms, scalable distributed consensus systems and interoperability mechanisms.
Unmanned Aerial Vehicles (UAV’s)
UAV’s include miniature helicopters, airplanes and multirotors that can be remotely controlled by human pilots on the ground or outfitted for autonomous navigation and used to perform aerial surveillance. UAVs typically incorporate GNSS, camera, sonar sensors and navigation systems that guide them for imaging, thermal and spectral analysis. Memory caches and communications links allow UAVs to collect and transmit datasets, as well as transfer them to the cloud for record or instance calculation.
More and more commercial applications for UAV’s are emerging, and there is an increasing number of investments made in UAV start-ups and big companies. Practical examples of commercial UAV applications include parcel delivery, pipeline inspection, disaster inspection, security inspection, and agriculture inspection.
Ben Ward 
