This capability is in high demand. “One of the biggest challenges businesses face when implementing a digital strategy is ‘faster implementation,’” said Mr. Duncan. In Gartner’s Digital Business Survey, 48% of respondents cited this challenge. Gartner clients report lead times of six weeks or more to develop and generate the business reports that are necessary to make business decisions.
Mr. Duncan advised: “Abandon hierarchical working practices, and build analytics teams with a culture of agility.” Here are his recommendations.
To be agile, analytics teams need to be configured in a way that enables members to dynamically adopt different roles. Factors to consider include:
- The team may function in a fully centralized manner, or in “virtual” collaboration, depending on the organizational culture and dynamics.
- Once in place, the team may move toward self-organization, where it will make its own decisions about who will fulfill roles to achieved required project outcomes.
- Resourcing levels may need to vary according to levels of demand.
- Other internal resources can be brought in when required.
Learn More: Understand the traits of a data-driven culture
Technical abilities are the cornerstone of analytics teams. But to operate in an agile manner, members of the team must have an innate predisposition for:
- Critical thinking and problem solving
- Bimodal work practices
- Rapid prototyping
Leaders entrusted with leading agile analytics need to create an environment where self-organizing team members can effectively operate and deliver value to the business. Agile analytics team leaders should be able to:
- Relate: Share business insights that build team trust
- Scout: Seek information from other stakeholders
- Persuade: Engage, support and encourage the team
- Empower: Delegate, coach and support team members
Mr. Duncan stressed that the term "agile" is used within the IT domain to describe a specific category of software development methodologies. “Agility within the analytics practice refers to a general ability to be responsive, flexible and deliver fast insights,” he explained.
“Analytic agility needs to be developed and embedded across three complementary analytics capabilities – the technology and architecture, the analytic processes and the skills of the analytics team” he said.”