Big data analytics has taken center stage in the digital economy. Big data is providing actionable customer and market insights, reflecting business performance, and empowering informed decisions.
According to IDG’s State of the CIO 2020 report, 37 percent of IT experts indicate that data and business analytics will be the driving force for most IT investments. Currently, this industry is worth $138.9 billion and is expected to reach $229.4 billion by 2027.
As IT leaders focus their attention on data analytics in 2021, they should keep key trends top-of-mind. We asked Chief Data Officers from different organizations to reveal their top trends in data analytics that will dominate 2021.
These CDO insights will inspire your data analytics strategies to take your organization from the uncertainty of 2020 into opportunities in 2021.
Process Mapping, Data Consistency, and Self-Service
Enterprise data is getting more dispersed and that trend is expected to continue in 2021. It’s more important than ever for businesses to leverage data appropriately, transform data into actionable insights, and continually empower teams within the organization.
Below are the top 2021 data priorities from Das Dasgupta, the Chief Data Officer of Saatchi and Saatchi.
Data Process Mapping
End-to-end data process mapping for all functions that can leverage data for actionable insights is becoming increasingly popular. Process mapping starts from the data strategy for audience segmentation, targeting, and positioning through data-informed creative and media planning. Organizations must also map available tools and vendors to understand what we have and what we need.
Data security is becoming a major challenge for businesses of all sizes. We expect to see more data audits for existing and new sources to help tackle major security concerns that may lead to data breaches.
Build and Upgrade Talent Pools
Another 2021 data analytics trend is focused on leveraging big data to build and upgrade talent pools. For instance, the Data-at-the-Center (DATC) team at Saatchi, which is under my office, comprises of five competencies, including Data Science, Data Engineering, Marketing Analytics, Return on Media Investment (ROMI), and Content & Platform Analytics (C&P).
Automation and Self-Service
Another major trend is automation and self-service for the user community, specifically in the delivery of insights and productizing templates. In our case, the user community represents Saatchi’s internal Strategy Team, Creative Team, Media Team, and their corresponding client teams (external). We’ll continue training all internal, as well as client functions, on the use of data to inform their decisions and change management for moving from awareness to usage.
Empower Brands with Best-in-Class Data Platforms and Flows
In the progressive data analytics arena, organizations are using advanced platforms to manage their digital presence and level-up their brand experience. Investing in the best data platforms and flows will be a key focus area for brands.
Cameron Davies, CDO of Yum! Brands, shares his perspective on 2021 data analytic trends.
In 2021, we expect to see more data governance, flows, schemas, and advanced tools that make better customer experiences happen. That means developing best-in-class data platforms and flows, enhancing eCommerce and Digital Platforms with AI/ML “Brains” to improve experiences and enhance economics, and empowering our brands with data-enhanced insights and analytics tools.
Focus on Digital Transformation and Data Mapping or Get Left in the Dust
Self-service and AI will be fully integrated into most aspects of the business environment, delivering heightened efficiencies and enhanced human capabilities. As AI and self-service technologies evolve, teams will continue to add more value to their organization and the people their organization serves through digital transformation.
Neal Linson, CDO at Incite Logix, highlighted the top trends expected to continue in 2021.
Organizations that are not focusing on AI in their roadmap are going to be left in the dust. If you wait, your business will be harmed, lose market share, or disappear altogether.
For most people, AI is a marketing term and “out of grasp…instead, they are calling it digital transformation. To build the foundation of context for AI capabilities down the line, AI must be at the center of your digital transformation. When you are going through digital transformation—and you call one entity something from one system to another—you create more technical debt and hinder AI in the future.
To keep up with the trend of digital transformation, IT professionals should direct their focus on information self-service. Start incorporating meta-data documentation and data ontology mapping as key pieces of your digital transformation requirements. CDOs should ensure their organizations have the basis to add AI into BI capabilities with an enterprise ontology and decide which application of AI, ML, or auto ML will most dramatically improve the business.
Investments That Turn Data into Intelligent Experiences
Data is the most valuable asset and what really makes it valuable is when users can utilize it to connect in the most meaningful ways. Investments in data foundations, machine learning, analytics, AI, and scorecards have enabled Microsoft’s Core Services Engineering to democratize and transform data into intelligent experiences.
Priya Raman, lead Data and Intelligence at Microsoft (currently Chief Data Officer at Coca-Cola) takes us behind the scenes to discuss key data analytics trends and strategies in 2021 and beyond.
The Data Escalator
Organizations tag less than three percent of data but analyze less than one percent of it. A lot of data is generated but often left to sit in silos….and it becomes difficult to discover.
Our main focus is to turn this data into intelligent experiences in what we call a “data escalator” that allows other users to find data easily, understand the quality of data at hand, and connect with it in a scalable and durable way to create real business impact.
As we grow to be a product-centric organization, it’s important to measure and understand what our users and business care about and create our products around that. Scorecards come in handy in such cases.
Frameworks such as HEART (happiness, engagement, adoption, retention, task completion) allow us to understand the engagement of our users with the products and experiences that we produce. These analytics helps us drill down to understand what works and what we need to improve.
Machine Learning, AI, and Governance
The next trend we expect to see is more advanced technology powered by machine learning and AI. Trusted and connected data is the backbone of creating intelligence. More importantly, it’s about infusing intelligence into what we truly want to impact.
As we democratize data, we need to ensure it´s consumed in a secure and trusted way. Data governance is critical to democratizing data in a responsible manner.
To Achieve Business Success, Be Bolder in Your Data Investment
Every day vast amounts of data are generated through multiple data streams from a variety of sources. Organizations are getting the most value out of their data by investing in it, whether they are focusing on data security and consistency or organizational training and technologies.
Frank J Bernhard is the Chief Data and Analytics Officer at large for several private equity operating companies—in 2021, he is emphasizing the following focus areas.
Readiness for good data governance means implementing data stewards that address conceptual and logical structures. To drive the value proposition, you have to be bolder in your data investment.
Never before has so much general consumer data been created through COVID. We have to do more with data, make sure we have model validation along with our data governance. We must have primal knowledge of the data to be successful in our AI design.
Getting a BI semantic layer for the business to consume the data is constant progress we are making on our DevOps. This helps the team understand priorities and continually enhance the model creation.
It’s also important to invest in more advanced data visualization capabilities at the end-user level so it’s easier for most people to understand how to use the data explicitly. It’s not all about investing in more tools. It’s about investing in our BI team and making more people involved to better communicate and provide ad-hoc analysis.
2021 data analytics trends will continue to drive digital transformation. Being on top of the latest technologies and best practices is essential to guide your organization on the right path to achieve success.
If you need guidance and support this year, get in touch with our expert team here at CSG Pro.