Ahead of its Data & Analytics Summit, May 22-24, in London, UK, Gartner Analysts discuss the latest trends that data and analytics leaders must keep up with to ensure they’re delivering maximum value to their organisations.
“The need to deliver provable value to the organisation at scale is driving these trends in D&A,” says Gareth Herschel, VP Analyst at Gartner. “Chief Data and Analytics Officers (CDAOs) and D&A leaders must engage with their organisations’ stakeholders to understand the best approach to drive D&A adoption. This means more and better analysis and insights, taking human psychology and values into account.”
Trend 1: Value Optimisation
D&A leaders must be able to articulate the value they deliver to the organisation in business terms. Value optimisation from an organisation’s data, analytics, and artificial intelligence (AI) portfolio requires an integrated set of value-management competencies including value storytelling, value stream analysis, ranking and prioritising investments, and measuring business outcomes to ensure expected value is realised.
“D&A leaders must optimise value by building value stories that establish clear links between D&A initiatives and the organisation’s mission-critical priorities,” said Herschel, a Gartner research vice president.
Trend 2: Managing AI Risk
As the use of AI grows, companies are exposed to new risks such as ethical risks, poisoning of training data, or fraud detection circumvention, which must be mitigated. Managing AI risks is not only about being compliant with regulations. Effective AI governance and responsible AI practices are also critical to building trust among stakeholders and catalysing AI adoption and use.
Trend 3: Observability
Observability is a characteristic that allows the D&A system’s behavior to be understood and allows questions about their behavior to be answered.
“Observability enables organisations to reduce the time it takes to identify the root cause of performance-impacting problems and make timely, cost-effective business decisions using reliable and accurate data,” said Herschel.
Trend 4: Data Sharing is Essential
Data sharing includes sharing data both internally (between or among departments or across subsidiaries) and externally (between or among parties outside the ownership and control of your organisation). Organisations can create “data as a product,” where D&A assets are prepared as a deliverable or shared product.
“Data sharing collaborations, including those external to an organisation, increase data sharing value by adding reusable, previously created data assets,” said Kevin Gabbard, Senior Director, Analyst at Gartner. “Adopt a data fabric design to enable a single architecture for data sharing across heterogeneous internal and external data sources.”
Trend 5: D&A Sustainability
D&A leaders must optimise their own processes for sustainability improvement. The potential benefits are enormous. D&A and AI practitioners are becoming more aware of their growing energy footprint. As a result, a variety of practices are emerging, such as the use of renewable energy by (cloud) data centers, the use of more energy-efficient hardware, and the usage of small data and other machine learning (ML) techniques.
Trend 6: Practical Data Fabric
Data sharing includes sharing data both internally (between or among departments or across subsidiaries) and externally (between or among parties outside the ownership and control of your organisation). Organisations can create “data as a product,” where D&A assets are prepared as a deliverable or shared product.
“Data sharing collaborations, including those external to an organisation, increase data sharing value by adding reusable, previously created data assets,” said Kevin Gabbard, Senior Director, Analyst at Gartner. “Adopt a data fabric design to enable a single architecture for data sharing across heterogeneous internal and external data sources.”
Trend 7: Emergent AI
Emergent AI will change how most companies operate in terms of scalability, versatility, and adaptability. The next wave of AI will enable organisations to apply AI in situations where it is not feasible today, making AI ever more pervasive and valuable.
Trend 8: Converged and Composable Ecosystems
Emergent AI will change how most companies operate in terms of scalability, versatility, and adaptability. The next wave of AI will enable organisations to apply AI in situations where it is not feasible today, making AI ever more pervasive and valuable.
Trend 9: Consumers Become Creators
As data and analytics become more accessible, consumers are seeking more personalised and dynamic experiences. The percentage of time users spend in predefined dashboards will be replaced by conversational, dynamic, and embedded user experiences that address specific content consumers’ point-in-time needs.
Organisations can expand the adoption and impact of analytics by giving content consumers easy-to-use automated and embedded insights and conversational experiences they need to become content creators. By doing so, they can provide personalised experiences to their customers and drive innovation.
Trend 10: Humans Remain the Key Decision Makers
While automation and AI are transforming the way businesses operate, not every decision can or should be automated. D&A groups are explicitly addressing decision support and the human role in automated and augmented decision making.
“Efforts to drive decision automation without considering the human role in decisions will result in a data-driven organisation without conscience or consistent purpose,” said Herschel, a Gartner research vice president. “Organisations’ data literacy programs need to emphasise combining data and analytics with human decision-making.”
