MicroStrategy World 2020 may be in our rearview, but now is a great time to start taking what we learned from the conference and figuring out how we can apply it throughout the rest of the year. For instance, how we can follow the trends that industry professionals are seeing in the field of analytics.
In his “Future Trends: Driving Analytics Adoption” session at MicroStrategy World, Ventana Research CEO and Chief Research Officer Mark Smith talked about analytics trends and driving adoption. Based on what we learned, here are 5 trends you can follow to maximize analytics adoption.
By 2020, 90% of business professionals and enterprise analytics say data and analytics are key to their organization’s digital transformation initiatives. – Research and Markets
Trends Driving Analytics Adoption
Using data and analytics to drive business decisions, better customer experiences, and overall digital transformation is a goal that most organizations share, but the path to adoption comes with challenges. While modern, cloud-based analytics and end-user self-service have helped increase adoption and the value of analytics, there are a few trends you can start following to bolster your success.
1. Embrace and Use Mobile Computing
Access to mobile analytics is greatly improving adoption and providing users with data immediately. Plus the widespread deployment of 5G will likely make access even faster and accelerate the mobile-first movement furthermore.
The voice and proximity on mobile provide personalized context to information. And Mobile computing with IoT and XR also provides augmented and virtual potential.
2. Embedded Analytics Everywhere
Users no longer have to switch between tools to find the data and insights they need. Instead, analytics can be integrated into a user’s day-to-day workflow. This seamless integration, enabled by Open platform, provides both internal and external users with immediate access to actionable insights inside of the applications and processes they’re already using in a context-aware manner.
3. Ensure Intelligence in Analytics
Embracing advanced, prescriptive, and predictive analytics tools is another driving force behind adoption. These tools can generate context and drive real insights. Specifically, using the Semantic model and graph to generate context and prescriptive and predictive analytics to drive real insights.
When generating context with advanced analytics, Semantic data modeling techniques are great because they can be used to define the meaning of data within the context of its interrelationships with other data. Basically, it can define how data relates to the real world. And this is key because users are more willing to see the value in analytics if insights are accompanied by context. Without context it’s difficult to take action and users are often left with more questions than answers.
Once users have context, predictive and prescriptive analytics can guide the next steps. It’s one thing to see the data, but knowing the story and suggested prescriptive action can make all the difference. Predictive analytics provides you with the raw material for making informed decisions, while prescriptive analytics provides you with data-backed decision options that you can weigh against one another.
Insights are worth a nickel, actions are worth a dollar – Mark Smith, CEO and Chief Research Officer, Ventana Research
4. Embrace NLP and Conversational Analytics
A general lack of data literacy among non-specialist users has made adopting analytics tools challenging, but improvements with natural language processing and conversational analytics are expanding the potential user pool. These tools remove the need to program queries into an analytics tool and make it easy to query databases. Conversational computing can process a large number of conversations (text and voice) at scale in the form of natural language processing and help bring immediate insights a lot more easily.
Furthermore, Gartner predicts that 50% of analytical queries will be generated via search, voice or NLP (or automatically generated) by 2020 and that NLP and conversational analytics will drive analytics and business intelligence adoption from 35% of employees up to over 50% by 2021.
5. Utilize Collaboration to Engage People
While a lack of data literacy is a challenge, so too is a lack of data democratization. Data and analytics play a key role in an organization’s success, but there’s a lot of missed opportunities if all staff members aren’t empowered to access, analyze, and act upon the information. Allowing staff companywide to inform on strategic decisions adds to the greater overall success of your business.
To empower your employees, Forbes recommends the following:
- Share the vision across the organization
- Emphasize “soft” skills
- Establish governance
- Focus on continual learning and improvement
- Develop a “data-first” approach
Takeaways for Analytics Adoption
Data and analytics tools have the power to help create or maintain a competitive edge in your industry, but the success of your data and analytics project depends on your people. Based on the five trends above, successful user adoption comes down to:
- Are your tools fast and convenient? Users are more likely to use analytics tools if they have easy access to them (mobile) and if they can find the data quickly (embedded analytics).
- Do your users have context and insight on how to take action against data? Users want quick, actionable insights that provide background information (advanced analytics) and suggested the next steps (predictive and prescriptive analytics).
- Do your analytics tools perform the heavy lifting? Users don’t want to spend an exorbitant amount of time programming queries or sorting through complex data. Allowing NLP and conversational analytics to do the hard work not only delivers insights more easily but increases the potential user pool.
- Do your users have visibility and knowledge? Democratizing data and providing all employees with visibility into data not only increases adoption, but also more informed business decisions. But granting access to data and analytics tools also requires proper training and education.
More Insights from MicroStrategy World 2020
Check out our other MicroStrategy World 2020 blog “Too Weak, Too Slow: MicroStrategy World 2020’s Big Theme.” We discuss how MicroStrategy is addressing the idea that existing enterprise applications were built for an outdated paradigm and are too weak and too slow to meet the demands of today’s users.
