Data driven decision making in the ‘new normal’ | Deloitte UK has been saved
Limited functionality available
Most of us could never have imagined the unparalleled effect COVID-19 is having on everything that we used to consider normal. Businesses that survive the initial crisis will have to navigate through the recovery period, which some analysts say will be even harder on balance sheets than the initial lockdown. Government and public services organisations are also having to reform and transform the way they operate due to the effects of the pandemic on the citizens they serve and staff and suppliers, often from the private sector, who deliver the services.
No one really knows how long the recovery will last or what shape it will take, but clearly we will have to find new ways to manage in what is sure to be a “new normal” post-pandemic.
Organisations need to perform complex analysis such as segmentation, eligibility, personalisation and trend and options analysis when delivering customer and/or citizen services. A startling fact, however, is that to get through this time, organisations might not be able to rely on their well-established decision-making tools and models. Tools like AI, machine learning, and predictive models won’t be able to function exactly as designed in this new normal. Why? Because they will be based on historic precedence in a time where everything will be different in unprecedented ways.
Weathering the new normal
The very novelty of today’s circumstances undercuts the use of tools that have been trained and optimised based on historic data going back several years. But one timeless truism is that the best decision techniques are based on the use of data. The more dynamic the variables and unpredictable the circumstances, the more important it is for organisations to make data-driven decisions. If data-driven decision making was a competitive advantage before the pandemic, now it is a tool for survival.
If historical precedence can’t help with the analysis of data, what will? The answer is “what if” scenario simulations – but with a twist – as most contemporary “what if” scenario simulations would have used historical data and patterns to predict.
The new, post-pandemic ‘what if’ simulations will need to work with much more dynamic data and much less of it—and answer very different questions.
Simulators will need to use a digital replica of the business and draw on algorithms that are better at working with lower data volumes and can calculate thousands or millions of possible outcomes based on the latest circumstances at any given point in time.
It’s similar to predicting the weather: the accuracy of long-term forecasts are low, while very short-term ones are high—but still not perfect. You use the weather forecast as a guide to make decisions on a day-to-day basis. Likewise, “what if” simulations will need to be run frequently as the business or market changes, which can be hourly or daily.
The viability of organisations adopting these new types of simulation-based tools to make decisions will depend on the following factors:
Investing in the new normal
While many organisations are operating digitally, few are likely to have the capabilities to develop new tools, and even fewer will have the funding—especially in these desperate times when cash is king. This is also true in the public sector where new government investments are likely to be focused on health and economic recovery while the budgets for other public service areas will remain the same or likely be reduced.
In the new normal, industries and governments will have to find ways to fund, develop, and utilise data and analytics tools that will drive businesses, markets, and society to recover and thrive. The following is a guide on how to navigate the new normal using new data-driven approaches:
If the pandemic has not imposed radical change already, in the future most businesses will need to reinvent or profoundly change their business models and ways of working to recover and grow again.
Thriving in the new normal
Without a doubt, the pandemic is forcing us to change the way we live and work. These are changes that under “normal” circumstances were near impossible to implement due to differences in politics and varying viewpoints within businesses. Now though, harnessing the power of data and analytics is critical to navigating the recovery from this crisis and arriving at a place where you can thrive. The new normal is about change—and that can lead organisations to be even stronger post-crisis than they were before.
Nadun has over 24 years’ experience in innovating and delivering complex data analytics and technology transformation to national and global clients. At Deloitte, he is the Lead Partner for Data Analytics & Artificial Intelligence (AI) in Public & Transportation sectors. He has developed industry scale AI solutions that are delivering unprecedented gains in customer service delivery, operational planning, execution and asset management. Nadun is a thought leader in explainable AI, Data Privacy, Ethics and Open Data. He runs the Deloitte Analytics Labs, an innovation incubator that specialises in the development of products & services which uniquely combines AI with simulation technologies. As a Respect and Inclusion Advisory Partner, he also leads initiatives to improve inclusivity in the workplace. Nadun is the President of the Management Consultancies Association (MCA).
Costi is the Global Analytics & Cognitive Leader. Having started his career as an academic in the field of Information Engineering, he has over 20 years of experience in delivering large and complex technology programs. His expertise includes artificial intelligence information management, software development, and IT transformation. Costi's experience spans both the private and public sectors, but he has focused on the public sector for the last 15 years. Within the public sector he has worked in both central and local government, helping organisations deliver IT enabled transformations, and more recently transform through the effective use of analytics, automation, and artificial intelligence.