‘Big data’ is a priority for organizations of all sizes and sectors. The most astute businesses are already exploring the commercial value they can derive from rigorously designed, modeled, and integrated data.
This evolving context has yielded a greater demand for skilled data analytics teams, and technology recruitment has adapted on a major scale. We have gained in-depth knowledge of the market over six years, seeing it become a focal point within a cross-section of industries.
Here is our expert view on what constitutes a high-performing data analytics team.
Analytics Strategic Team Structure
Many companies fall into the trap of hiring data scientists without leaders, failing to achieve desired results. It is imperative that an organization invests in a senior leader to develop a structure and road map for data capabilities. This strategy requires sourcing talent with both strategic and technical expertise, creating a balance of data engineers, analysts, and data scientists. These professionals must possess the commercial experience to ensure data models are properly implemented and effectively communicated.
Analytics Effective Model Development
While transparent reporting lines are important, the principal aim of any successful data analytics team is to create effective models. It takes a unique skill set to build and implement models that demonstrate business impact and create actionable insights. Data scientists should be able to clearly articulate results to professionals across the organization, working in close collaboration with all functions.
Driving Commercial Business Acumen
There must be a focused commercial rationale behind model development. The best teams adopt a business-first mentality, focusing on executive-level problems and how data analytics provides appropriate solutions. Telling a story with data to stakeholders who have differing agendas is a key contributor to continued success.
Centralized vs. Segmented Infrastructures
Data teams must be carefully embedded within an infrastructure to perform consistently. Centralized teams tend to run analytics in ways that reflect the overall operation, while segmented teams mine data on a regional basis. Both have merits; it is about finding the right route for your specific data strategy.
Currently, the most successful teams are rooted in clever hiring, technical aptitude, and solid communication. The most common challenge is sourcing talent that unites technical experience with business acumen.
The Future of Data Analytics
Oliver James expects requirements to become more intricate as the market adapts. We project that data volumes will continue to amplify thanks to the IoT and internet-connected devices. We also anticipate a rise in companies appointing Chief Data Officers and Chief Analytics Officers to answer the need for distinct hierarchical structures.
As data analytics becomes more industry-agnostic, the sector could face challenges regarding privacy and business ethics. Issues ranging from Fair Lending Act violations to data procurement and third-party utilization will require illuminating answers in the coming years.
Businesses effectively utilizing data will be more productive, better able to target products, and increase customer loyalty. Right now, the biggest fear for an organization is investing in a team that provides no business value.
Partnering with a Trusted Expert
It is important to partner with a recruitment agency that understands where the market is headed. Our data specialists attend regular conferences and technical seminars to stay abreast of the latest developments. We go beyond recruitment to understand your overall business aims, offering strategic insight into the marketplace and competitor activity.
