Using Data and Technology to Create Value in Your Organization

We are living in disruptive times driven by uncertainty, volatility, and ambiguity. People tend to forget quickly, but looking back, disruptive events are increasing over time. Remember the real estate crisis in the ’90s and the .com bubble in early 2000? What about the events of 9/11 and the financial crisis in 2008? And more recently, the Chinese stock market crash in mid-2015 and Brexit, just to name a few. During each event, leaders across the globe experienced sleepless nights, and companies went bankrupt. Every time, a new and unseen element was part of the disruption, but many things remained the same.

Uncertainty will not disappear—markets are more and more volatile, and the speed at which we see ambiguous events coming is only increasing. Companies must be proactive in assessing their capabilities to withstand disruption and the options they have to identify and respond to upcoming opportunities and risks. The need for dynamic, scenario planning has never been greater. Our world is moving fast, planning processes and tools need to follow. I believe, when times are disrupted we are forced to completely re-look at what they do and the way they do business. Technology and data will play a drastic role in future digitized planning processes.

The greatest danger in times of turbulence is not the turbulence; it is to act with yesterday’s logic - Peter Drucker

The Importance of Technology During Uncertain Times

People agree—planning during disruption is important. Following Deloitte’s point of view across the resilient drivers of respond, recover and thrive, planning during disruption is important in the short-term (to respond to the situation), mid-term (to recover from the situation), and long-term (to thrive and adapt to the new normal). This includes a big focus on cash flow planning and liquidity management, supply and production planning to meet new or different demands, and collaborating very closely with suppliers. It also includes cutting all non-crucial OPEX costs, reviewing which Capex investments can wait, analyzing the demand impact, adapting territory and quota plans, and plan proportions to recover and push demand. Companies should focus on new and innovative product launches to generate revenue in streams, ensuring you have the right resources available at the right place (workforce planning). And every single time, they should be running and re-running scenarios.

Running scenarios is easier said than done when it takes you a week to analyze the impact of one scenario on the top and the bottom line of the P&L and balance sheet. This is often the in legacy solutions where function works in siloes. That’s a hard situation when you need to analyze the impact of an event across the organization. Companies need a collaborative way of working together, a modular approach with driver-based models, all connected to each other in real-time. They need an agile Connected Planning solution with an in-member calculation engine that can calculate the impact of a single measurement across an organization in seconds. Making a decision fast is important. Making a well-planned decision is critical.

In a few short days, a scenario planning process can be transformed into a stable modular solution, leading to a fully-connected plan in just weeks. This was true at Deloitte when the team was able to analyze 37 scenarios spanning workforce, revenue, margin, costs, and cash flow in just 10 days with Anaplan.

The Need for Data and Analytics

No modeling could have predicted the situation facing companies. Still, I believe data and analytics are required more than ever. Much disruptions have impacted our models, but we still know that predictive analytics help residue the time we spend on forecasts through past learnings. Those who remember their statistic classes understand the need to think probabilistically. We are exposed to distributions where it is possible to see predictions that did not fit in the confidence intervals.

Still, advanced analytics can bring massive value. During uncertain times, it’s very important to understand what is happening around you. You need to observe how the markets are reacting, recognize trends, and acknowledge how interventions are affecting the market. Many companies have a blind spot when it comes to understanding what will happen as they only consider internal data. It’s external data—like macro-economic indicators, consumer sentiment, buying power, export, employment, IoT, and demographical data—that help you understand how markets are evolving. You can observe the most important external leading indicators, or you can leverage machine-learning models that correlate your organizational data through all the leading external indicators available and provide a set of specific indicators for you to monitor.

The end result is not an accurate picture of tomorrow, but better decisions about the future - Peter Schwartz

Predictive analytics support companies recovery from a disruption in the market by helping them understand how economic, industry and consumer trends will affect future business outcomes. Regression models are off when something extreme happens, but the correlation and causation factors are not disconnected. Once markets are more stable and lead times are re-established, a machine-learning-driven time-series model will help the organization identify inflection points, headwinds, and tailwinds for each region and product. By embracing data and advanced analytical techniques, and embedding them in your Connected Planning process, you will predict where demand begins and how quickly. Your supply chain and workforce will be prepared for recovery, also having the ability to tap into big data from other regions. Especially in today’s disruption, we can learn a lot by incorporating daily or weekly sales data across different industries from China and Italy.

Additionally, these models are giving us the ability to incorporate the recovery from recessions in our forecasts for long-term planning. Gartner is teaching us that especially macroeconomic leading indicators are very helpful to predict our business performance for the next 18 months while internal data (microeconomic data) are only explaining the short term.

It will always be a challenge to plan and forecast during disruptive times. There is no single solution or approach that provides all the answers. However, the last thing companies should do is nothing at all. Appreciate the value that data and technology bring and understand where in your organization it can create the most value. There is an opportunity in every challenge, and it’s up to everyone to take the opportunity and set the first steps towards more connected and data-driven enterprises.

If you want something new, you have to stop doing something old - Peter Drucker