The world’s biggest commercial brands and consumer technology companies are constantly being challenged and upended by disruption. The same is true in the B2B world. In fact, a recent survey revealed that 85% of enterprise decision-makers feel they have just two years to make significant inroads on digital transformation before suffering financially or falling behind their competitors.
For enterprise organizations, a digitally transformed future must be a data-driven one. Whoever can use technology to transform the customer experience and be the first to discover and deliver on new business models will be the disruptor. Those who can’t will be disrupted in this period known as the “era of Digital Darwinism”. Here are five key trends that enterprises should keep in mind as 2018 unfolds:
1. Artificial intelligence and machine learning will reshape analytics infrastructure
According to big data influencer Ronald van Loon, 2018 will be the year business intelligence and data analytics vendors incorporate mainstream AI and ML functionality to their suite of digital offerings on a global scale. I couldn’t agree more. And I will take the trend one step further by predicting that the enterprise will work to define what AI and ML actually looks like for specific industries, including manufacturing, healthcare, finance or transportation. Vendors will focus AI and ML innovation efforts on fitting the specific needs of the business customers they serve, boosting the productivity of customer workforces and the automation of repetitive tasks currently taking up a significant amount of customer staff time. Data analytics will be at the heart of it all.
2. Voice and natural language interfaces will become mainstream
There is a lot of attention around voice-driven technologies in the enterprise and consumer business worlds with the rise of Alexa, Siri and other increasingly scalable voice assistants. ComScore predicts that 50% of all online searches will be voice-driven by 2020. Meanwhile, natural language generation has begun to make its mark.
As Ventana Research’s David Menninger noted, “a written summary can be consumed by all and reduces the ambiguity of many types of data displays. The enterprise has been more consumed with providing maps and geographical displays as part of our information systems. Our research revealed that users consider text more important than maps.” Consequently, organizations should explore voice and natural language options and find ways to incorporate them into offerings to maximize the return on technology investments over the next year.
3. Competition for data science and analytics talent will heat up
A Business Higher Education Forum (BHEF) and PwC report predicted that there will be 2.7 million job postings for data science and analytics roles. Many of these will not be traditional engineering, operations or IT roles. These will be spread across the entire organization. As the shortage for those with data science and analytics skills begins to grow throughout the year, enterprise organizations will need to couple their recruitment efforts with dedicated retention initiatives. For enterprise organizations to have the talent they want as competition heats up, companies – especially those that traditionally acquire companies to boost offerings – also need to grow their own talent in-house with training and education to bridge an emerging data talent gap.
4. There will be a (re)convergence of real-time and batch-based analytics
In today’s enterprise, the real-time and batch-based analytics worlds have become disconnected. Real-time isn’t (just) what’s in the stream, but includes streaming and processing historical data as well. People with real-time analytics must compare it to historical data in order to conduct business.
Let’s imagine a retail store using sensors to measure and monitor traffic in real-time. With historical data, the analytics application can predict the most profitable product categories, and by combing the real-time distribution of customer traffic, sales personnel and historical sales, it can recommend the optimal distribution of sales people. More organizations use and store data from multiple sources (structured and unstructured), and they need to be able to act on it in ‘real-time.’ The fusion of real time data and analytics from historical data will enable a host of new use cases for actionable analytics throughout 2018.
5. Convergence will expand to vendors, emerging tech and enterprise tools
Over the course of the next year, emerging technologies including AI, VR, AR and net-gen analytics will continue to overlap and merge to achieve truly augmented intelligence. Machine learning will only reap its full value on big data that’s structured or semi-structured. Voice and smart bots will require AI to truly bring transformative experiences to users expecting specific answers from vast amounts of data. Telemetry data from enterprise systems will generate digital identity information that only big data storage will be able to capture – and only next-gen analytics will be able to take advantage of that telemetry data to provide answers and analytics based on proximity. The intersections will be various, but the evolution of each technology will increasingly rely on other technologies around it to deliver real value.
Additionally, we’ll continue to see organizations standardizing platforms on which they base their respective analytics ecosystems. They will focus on merging as many projects into that platform as possible. The traditional enterprise will become the intelligent enterprise – able to detect regulatory, technological, market and competitive challenges and proactively turn them into business successes or opportunities. Enterprise executives will see their businesses running on reliable data powered by emerging, analytics-driven technologies. Companies will have fewer tools to manage and pay for, the governance they need, and happy business users working alongside them to digitally transform their respective businesses in 2018 and beyond.
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