The Right Self-Service Analytics Can Strengthen Every Decision Maker
In today’s fast-paced and tumultuous world, businesses rely on frontline workers to make quick, intelligent decisions based on the latest information. Agility, precision, and fast responses all rest on the decisions and actions made by frontline workers, whether they’re responding to an online query, offering a customer discount, or selecting a supplier to reduce supply chain risk.
Research by Harvard Business Review Analytic Services makes clear that businesses can substantially improve business performance by giving frontline workers modern self-service analytics tools to enable fast, intelligent action. But it also reveals that not all self-service analytics provide such effectiveness broadly.
Moreover, just arming frontline workers with self-service analytics isn’t enough. The cultural and other challenges involved with providing such tools are often difficult for organizations to overcome.
Why Self-Service Analytics Matter
A new Harvard Business Review Analytic Services report, “Empowering the New Decision Makers to Act with Modern Self-Service Analytics,” examines the essential elements of modern self-service analytics from a tools-and-usage point of view, to the ways s organizations can hurdle the obstacles they face when entrusting frontline workers with these tools to take fast, intelligent action.
The report cites a May 2020 survey of 464 business executives by Harvard Business Review Analytic Services that reveals significant performance improvement among those respondents whose organizations had empowered frontline workers with digital tools to make good decisions in the moment. Among this group of respondents, at least one-third of them reported noteworthy improvements in both customer and employee engagement and satisfaction, as well as in product/service quality.
In the same survey, respondents named self-service analytics as a top technology they’d adopt by 2022 for their frontline workforce, second only to unified communication/collaboration tools.
Not All Self-Service Tools Are Created Equal
However, in another Harvard Business Review Analytic Services report, this one in January 2022, it becomes clear that not all self-service analytics tools are alike. For instance, tools that produce static dashboards, require days-long training courses, and rely on drag-and-drop data visualization can slow down insights, be difficult to work with, produce out-of-date insights, and deter frontline workers from using them.
As the report shows, frontline workers need to query data similarly to how they’d seek information in their daily lives: through a search-based interface that uses natural language processing capabilities and works across a wide range of the latest customer and business data.
Using this type of modern self-service analytics tool, frontline workers can easily, and thus quickly, word their questions in a natural and familiar way. They can pose their queries and drill down on the data easily, intuitively, and independently. The back-and-forth with data teams is eliminated, greatly reducing the wait time for insights and decision making.
Further, frontline workers themselves have the best knowledge and business context to dig deeper to get answers that are useful and make sense. With modern self-service analytics, these new decision makers can keep posing queries until they get the granular insights they need to drive better customer experiences.
Real-World Benefits of Search-Driven Analytics
Armed with higher-quality insights and their own skills and business knowledge, frontline workers can be fully confident in making decisions and taking fast, relevant action. According to Randy Bean, founder and CEO of advisory firm NewVantage Partners, modern self-service analytics boost speed, efficiency, accuracy, and trust in the insights that frontline workers glean from customer and business data.
Organizations are already using an intuitive, natural language approach to scale intelligent decision making across the enterprise. For instance, global health care technology company Medtronic’s data team has gone from answering 100% of procurement users’ analytics questions to handling just 20% of queries, with the business users themselves taking on 80% of their own data analysis.
And when a freak snowstorm hit Dallas in early 2021, frontline workers at the company were fully equipped to answer questions on how that would impact anything in the supply chain coming from Texas.
Overcoming Cultural and Organizational Challenges
Still, many organizations struggle with the organizational and cultural challenges of providing frontline workers with self-service analytics. In fact, these challenges are often more complex than those related to the technology itself. Issues range from breaking down data silos to change management to educating users on the benefits. Until they see how intuitive the tools are to use, and their productivity and efficiency advantages, frontline workers may resist adopting them.
As the report discusses, the most important action for businesses to undertake is to boost data literacy, both among frontline workers and across the enterprise. To achieve such literacy, some organizations are forming data enablement teams to provide continuous support, while others are providing online learning classes or on-site training.
Overcoming the challenges to empowering frontline workers with self-service analytics will be essential for any organization intent on achieving the key business capability of our time: a truly data-driven culture. As the report concludes, by equipping frontline workers with a modern approach to self-service analytics, organizations can operate with the agility, intelligence, and real-time actions needed for success today.
