Initially, pulling in all the necessary data will require a daily or weekly refresh. Evolve data systems so that data can be refreshed automatically.Using a collaborative team approach helps deliver robust, scenario-enabled modeling that is fact-based and supports real-time decision-making. Establish a team solely focused on forecasting.Ī cross-functional team can establish a process for continuous updating of data and ongoing evaluation of demand and supply shocks.
Forecasting and demand planning free#
Once a company has defined the necessary data inputs and ways to free that data from organizational silos, they can: That needs to flip in the current environment.
Forecasting and demand planning update#
These systems can regularly update the data for the finance and strategic forecasting teams, identify when foundational assumptions may have become questionable, and enable key decision makers to make informed choices more quickly.Ĭompanies have typically spent 80% of their time on financial planning and 20% on analysis. But we also know that in some cases, data is difficult to access because it is created and stored in business units, geographies and organizational functions and often outside of the corporation’s systems.Ĭompanies need to establish a culture of quickly sharing data across the organization and put the systems such as centralized dashboards and alerting systems in place. In some cases, as mentioned above, the reason is likely that the data they have relied on in the past is not sufficient for the future. When those that answered “all of the above” are included, more than three-quarters of participants saw access to meaningful and quality data as a significant issue. Identify where the data sits and “free” itĭuring our webcast, 44% of participants said access to meaningful and quality data was one of their biggest impediments to timely and accurate forecasting. The result was more accurate forecasts that are now updated in hours, rather than weeks. Their finance team then performed a regression analysis to see which metrics would show causation. Among the inputs they chose were weather data, cell phone tower data, social media mentions of their products and ZIP-code level unemployment data. One consumer company we worked with brainstormed to decide which data they needed to augment their typical syndicated sales data and other inputs to develop a more accurate, timely forecast. Outside data on pandemic hot spots, weather data, government regulations, mobility data, consumer sentiment and other measures can be run through regression or more advanced artificial intelligence (AI) neural network models to see what can best be used to augment and inform company forecasts. In some businesses, social media analysis can be used to improve data forecasting. For example, low gas prices would normally correlate with increased restaurant traffic, but that relationship has obviously broken down. The information used in the past may have become too static, too imprecise or no longer predictive. Knowing their customers have become even more important as their circumstances and behavior have massively changed, how should companies adapt? Change your data analysis techniques Companies can take several steps to change how they forecast. This means that waiting for the market to return to normal conditions as if it will be a V, U, L or W-shaped return to the demand curves can miss the bigger changes happening in the market. To prepare for these changes, forecasting must become a core competency, with an emphasis on analyzing data from multiple and sometimes novel sources to understand not only your customers’ plans, but also the potential change in who your customers are and how you deliver value to them. The challenge is that the intensity and length of each phase is still unclear, and we will see changes in customer demand across each phase. Even beyond the medical recovery, human movement and interactions may return, but in completely different patterns and ways that shift entire industries to new models. The COVID-19 recovery will move through medically defined phases a three-year plan could change in three days, based on when the spread of the virus slows (now), when companies can ramp up reopening, especially as testing and tracking protocols can be put in place (next) and, eventually, when there is immunity, either through vaccines or herd immunity (beyond). Unlike past downturns, the current crisis is both an economic and a medical one. The pandemic recovery will be driven by medically defined phases