Value through data-driven decisions

A number of activities are involved through the maturity process of large enterprises intending on leveraging data and analytics as a core driver within the organisation. Although technology and automation play a role, it comes down to how it’s adopted, used, and informed by core business stakeholders and value-focused metrics.

Data-driven transformation

Artificial intelligence (AI), machine learning (ML), and data science buzzwords are creating pressure for all established enterprises to remain relevant, and retain and grow their market share, through digital channels, innovative interactions – and most importantly – leverage data.  

The current data landscape: Before embarking on new initiatives, a comprehensive understanding of the state of data needs to be considered. What data assets do we hold? What is the quality of these assets?

Data sources and ingestion: Constructing an understanding about where data comes from and where it’s used for functional and operational purposes, as well as informing business decisions. Which channels, systems and processes produce data, and which consume data?

Understanding the data: Data is almost always nuanced. Useful analytics requires useful data to begin with. Missing data fields, non-conformity in data values, and poorly related data can kill any initiative before it starts. This must be uncovered and addressed early.

Stability and static reporting: The typical reporting that most enterprises are accustomed to are static reports generated on a regular schedule. Although these are useful for informing decisions, they’re sometimes nuanced in that they require manual intervention, or the frequency is not conducive to nimble decision-making or automation.

Dynamic reporting and dashboards: Once data can be meaningfully related, processed, and surfaced into useful artefacts, the organisation can start looking for areas in visibility and decision-making where real-time reporting and dashboard can be leveraged for efficiency.

Integration into business processes: Business processes are usually well-established and dated, but work to keep the wheels turning. However, as the digital age progresses, fast adaption to market needs is crucial to remain relevant. Value propositions should be mapped and reviewed, and mature data insights should be accurate and accessible in informing changes in product and service offerings or operational processes.

Integration into digital offerings: Organisations that truly embrace data, knit it into the core of their offerings. Data can adapt offerings on digital platforms in real-time based on the ever-growing knowledge about customers, their behaviour, and their needs.

 

For established enterprises, generating value through data has huge potential – especially given the amount of data available to better inform activities. The challenge is that this cannot happen overnight. A diligent and incremental approach must be used to tackle this problem – it’s a marathon, not a sprint. Close collaboration and buy-in from key business representatives and business subject matter experts will determine the success or failure of any transformation initiatives. A clear strategy must be outlined in how technology will support business functions, and elevate them and the people involved, over simply replacement and efficiency.

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