PwC six step guide to data and advanced analytics (COVID-19)
An agile response to the COVID-19 pandemic has seen some global companies flourish while many flounder. According to a report by Pricewaterhouse Coopers (PwC) the global pandemic has been the catalyst for a rapid digital transformation.
Cutting-edge companies that had invested in advance analytics and streamlined data were agile enough to predict the needs of the consumer during lockdown, supplying everything from home gyms to hot tubs. But many other companies were unable to adapt to the abrupt change in consumer choices and demands.
The COVID-19 pandemic should be a wake-up call for companies that have yet to start their information value chain evolution or have been idling at an early stage.
Be prepared: Companies have now recognised the urgent need to invest in and enhance their data and analytics capabilities to ensure an agile response to future challenges before they spiral out of control and identify new opportunities before someone else takes advantage.
“Whether leaders thought they could wait, or thought they could get by with less sophisticated capabilities, or were unsure how and where to start, they now see that transforming information into insight will be key to reinvention”, claims the report.
Six steps of transforming information into insight
- Business decisions and analytics: Prioritise analytic insights that fuel the business strategy.
- Data and information: Integrate multiple data types and let the data tell the story.
- Technology and infrastructure: Build tools that support the analytics ecosystem, including AI, and democratise insights through analytics.
- Organisation and governance: Establish the use of governed data and analytics.
- Process and integration: Ensure insights are rapidly integrated into decisions through an agile process.
- Culture and talent: Instil a data-driven culture that blends business knowledge and analytics insights across all levels
In the first stage, companies generally begin to accumulate significant quantities of data but it is labour-intensive. They tend to have some of the technology and infrastructure needed to support analytics but usage is typically limited.
This often leads executives to view the road to information maturity as too daunting and still rely more on expert opinion to make decisions. The data and analytics system are not yet delivering business insights.
Companies can move to stage two when there is a clear connection between business decisions and analytics. By the end of this stage, companies should have a centre of excellence that delivers insights to stakeholders. This has allowed leaders the foresight to see disruptions coming and to make data-driven decisions to prepare for them.
A focus on process and integration along with culture and talent will move a company to the third stage in which data and insights are transparent. Leaders view the business as a “knowledge company,” with analytics and insights embedded in the decision-making processes. Companies need a digitally upskilled workforce prepared to adopt the new tools and technologies.
Certain elements will play a more visible role at different points along the maturity scale but excellence in all six is needed to realise the full value of a data and analytics transformation.
When companies have reached peak maturity, many types of data are brought together. A rich variety of algorithms and AI/ML tools put all this data to work, and extract insights beyond the capacity of the human brain to tell stories that would otherwise remain hidden.
The report from PwC concludes the three steps to transform information into insight consists of; “what” (accumulating information that shows what happened), to the “so what” (insight that explains why it happened), to the “what next” (either to prepare for challenges or capture opportunities that were not obvious).
By increasing maturity and sophistication of data and analytics will allow companies to adapt to change before it happens.
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