In an era of digital transformation, growth in data is creating an environment where organisations need to adopt robust analytics capabilities just to keep pace. To prepare for the uncertainties expected to arise from this evolving landscape, many organisations across industry sectors are starting to recognise the need to make decisions, driven by insight, in order to foster a competitive advantage.
Leading organisations are those taking the evolution of analytics one step further – moving beyond traditional methods of capturing data and insights to transform themselves into insight-powered enterprises with the robust analytics capabilities necessary to maintain a competitive advantage in the uncertain landscape.
To explore ways for organisations to build and sustain analytics capabilities, Accenture conducted an Analytics Operating Model Benchmarking Study, which aimed to determine best practice across leading organisations and set benchmarks for improvement for organisations with lower maturity in analytics.
Leading organisations look beyond the traditional methods of data analytics and consider ways to attain the most value from their data in order to foster a strategic competitive advantage and have a leadership team willing to make a true commitment to improving analytics measures.
According to Accenture’s research, these organisations with mature analytics operations generally share five key characteristics. Organisations that are less mature in their analytics operations should look to adopt these characteristics in order to learn from and keep pace with industry leaders.
- They establish a centre of gravity for analytics – According to Accenture, analytics leaders are more likely to have an established centre for analytics activities embedded into the organisation, often in the form of a Centre of Excellence (CoE). Leadership also has a role to play, with nearly 40 per cent of those companies surveyed revealing they elevate their analytics by creating a Chief Data and Analytics Officer (CDAO) role, responsible for both the vision and implementation of the enterprise analytics strategies.
- They create an inter-disciplinary, high performing analytics team –Organisations with advanced analytics capabilities require teams with diverse skills. It remains difficult, if not impossible to find individuals with all the skills required for analytics success. To overcome this, many mature companies are establishing ‘pod’ teams with a mix of roles, including data scientists, analytics modellers, visualisation experts, data engineers, business analysts and business domain experts.
- They deploy new capabilities faster – Leading analytics organisations deploy new, agile technologies, as well as hybrid architectures and specifically designed toolsets, as a means to help achieve desired outcomes. One distinguishing characteristic of fast-moving companies is that they pilot with the intent to scale; that is, they establish the right mindset, processes and accountability in advance, then move quickly to test, learn, refine and implement.
- They work to raise the company’s analytics IQ – Leading organisations, for example, implement an Analytics Academy to provide analytics training for functional business resources, in addition to core management training programs.
2. They employ ‘agile governance’ –Today’s high performing analytics leaders are building thin, horizontal governance structures focused on outcomes and speed, rather than creating hierarchies that are slow to adapt. These structures take a ‘test and learn’ approach to rolling out new capabilities and a structured approach to innovation, where teams focus on addressing key business questions for a concentrated period of time. Perhaps the most critical part of establishing an agile governance structure is ensuring it uses the key metrics most important to improving business performance.
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