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Knowledge is power: Business forecasting in the cloud

(Image credit: Shutterstock / aorpixza)

2020 has been a year of uncertainties and issues that are not likely to disappear anytime soon. The pandemic brought a multitude of challenges we have never seen and therefore could not prepare for. While some firms were able to rapidly respond to the crisis with remote working, many businesses have been left struggling by lockdown after lockdown and the necessity of social distancing measures. Despite hopes of a light at the end of the tunnel, it is still unclear how much further we have to go before our businesses can get back on the straight and narrow.

The coronavirus has not been the only source of uncertainty this year. The ongoing unpredictability of Brexit continues to leave even the best-prepared firms in the lurch, unable to predict how the transition will play out and what its impact will be in the short and medium term. It’s possible that Brexit will only prolong the economic hardship and uncertainty facing businesses and the country. The question, then, is what can firms do in the face of these unknowns?

Previously, firms relied on business forecasting based on large data sets to model what lies ahead. However, these models have become near useless in the current climate, due to the unprecedented nature of the many challenges facing us. Businesses’ only option in this scenario is to completely rebuild their prediction tools with fresh data. It is possible, with cloud technology, AI and automation, to accomplish this – but it’s still a race against time to bring businesses out from the shadows.

The unknown unknowns

Businesses should make use of every tool in their arsenal. It’s important to distinguish between forecasting, scenario modelling and planning. Forecasting is the act of predicting where your business or the market will be at a point in the future based on relevant historical data. Scenario modelling is when analysts create a range of likely scenarios by looking at possible key turning points. Planning represents the measures and decisions you make based on those insights. 

Forecasting and scenario analysis feed the planning process, making them crucial early stages in adapting to disruption. Yet forecasting has become extremely challenging in the current environment. 

Forecasting depends on massive amounts of first-party and public data, but COVID-19 has brought businesses into unknown territory. McKinsey data shows that businesses remain divided on the shape of the pandemic recovery, with outlooks shifting towards a muted, slow recovery. We lack the historical data we’d normally depend on to analyze a crisis, and we also lack the trends that would help forecast what conditions will be like once disruption has passed.

This is where scenario modelling comes into its own. Scenario modelling helps businesses visualize a wide range of possible futures, plan for multiple scenarios and assess how to respond to each one. While the process still depends on data, it doesn’t require historical data relevant to a particular scenario. Instead it presents a range of likely outcomes that businesses can prepare for. It’s the ideal antidote for a future where little in certain.

However, recent experiences suggest the need for a more mature approach to scenario modelling. Despite many organizations actively modelling future scenarios before the crisis, few foresaw or were able to plan for the pandemic. You can’t plan for every outcome, but businesses should start investing into a wider range of possible scenarios going forward. Setting up dedicated analysis teams in each department can help bake scenario modelling into business processes.         

A new era of predictions

More regular, comprehensive scenario modelling won’t be enough by itself to guarantee resilience. As time passes, organizations will collect more and more data that facilitates traditional forecasting. Both methods of prediction are necessary to help businesses plan for the future. Yet both can also be easily undermined by the quality of data and systems in an organization.

Massive amounts of data concerning customers, employees and competitors can be difficult to manage. Often it will be segmented across an organization, divided into numerous silos that prevent it from being analyzed together. Planning for disruption needs a coordinated response, consultation and collaboration, but it’s difficult to achieve when plagued with silos.  

Speed is another issue. The time it takes to perform manual and unnecessary tasks – including data cleansing or entry for analysis – is precious time wasted. It becomes a case of wasted resources, but it also means the organization may be too slow to respond to rapidly emerging trends, challenges or opportunities.

Companies can make the task easier by leveraging cloud tools and applications. Many businesses are doing this already – Gartner expects cloud spending to increase by 19 percent in 2020, a rate of growth it hadn’t expected until 2023. Centralizing your data estate in the cloud encourages collaboration because workflows and data reside on one rather than multiple systems.

Consolidating forecasting activities in the Cloud also instils more confidence in the process as everyone is using the same methods and tools. Cloud applications can be updated to the latest best practices regularly, so processes are always up to date for all groups.

Embedded AI apps and solutions can greatly accelerate forecasting and prediction by automating manual data processes. This contributes to agility because people spend less time gathering and verifying data and more time planning for disruption. With the right information sooner, executives and lines of business can make decisions faster and with more confidence.

Predictions build resilience

This year will go down as one of the toughest years for business in recent times, primarily due to the unpredictable nature of the situation we face. Traditional tools to prepare against hardship simply cannot handle the unprecedented nature of Covid-19 and Brexit. But where old technology fails, cloud and machine learning offer new hope. Predicting what lies ahead is crucial for the survival and prosperity of every business, no matter which industry. The challenges of this year are not yet behind us, and it is crucial to take the steps now to stay ahead of them in the year to come.

Angela Mazza Teufer, Senior Vice President of ERPM, Oracle Western Europe (opens in new tab)

Angela Mazza Teufer is Senior Vice President of ERPM for Oracle Western Europe. She is responsible for growing the ERPM market share in the region.