Can You Lead?

Supply chain organizations are discovering the benefits of integrated business planning.

By Neal Goffman

Executive teams need accurate forecasts to set performance benchmarks and optimize targets for revenue, profit, territory, pipeline opportunity and more. Production and procurement teams need them to optimize required resources such as raw materials, people and equipment. Finance needs them to weigh capital investments against liquidity needs. Wouldn’t it be great if every functional team in the organization could share the same, statistically derived, continually updated, cloud-based demand data?

Fact is, too many organizations still email spreadsheet updates and manually aggregate inputs from sales teams based on gut-feel assumptions. Other organizations rely on Enterprise Resource Planning (ERP) applications or other transactional databases to inform their monthly or quarterly Sales and Operations Planning (S&OP) meetings. These systems, though highly valuable, are simply not geared for forecasting and planning. Truth be told, the manual and non-statistical processes associated with both spreadsheets and legacy BI systems are error-prone, labor-intensive, and generally ineffective for forecasting and planning.

Predictive to Prescriptive Analytics

Accurate demand forecasts underpin successful planning enterprise-wide, from sales and marketing to production and inventory. Many data-mature organizations have already invested in advanced analytic applications that bring these two ends of the business together – sales and operations – in a unified environment.

Such applications markedly increase forecast accuracy while automating the forecast process and slashing labor time. Some of the higher-end tools also run optimization algorithms that can effectively prescribe best-actions that take into account business policies and rules under virtually infinite sets of parameters, constraints, or business scenarios. So-called Monte Carlo simulation is one such technique to what-if test an unlimited number of scenarios to reveal whole ranges of potential outcomes, including the probabilities of each. This is the stuff of not just predictive analytics, but prescriptive analytics, in which information technology is geared to optimize all facets of management decision making.

Finally, best-of-breed applications can also now fully integrate financial forecasting into the demand-supply planning process. Done on a rolling basis, financial integration enables organizations to run truly “evergreen” processes for what many analysts refer to as integrated business planning (IBP).

The returns on investment in a well-implemented IBP software platform are numerous and extremely high in value: lower inventory costs and improved service levels, reputation, customer loyalty, cash flow, investment timing, and top and bottom lines.

Workflow and Worker Knowledge

The last piece of any best-in-class forecasting and planning application is the ability of knowledge workers to not only make use of advanced-analytic forecast tools, but to fine-tune forecasts with insights only found within the employee base (not found in the data). This could include a business user’s knowledge of a new competitor, a forthcoming product release, an unexpected order or a cancelled customer contract. It’s important to note that any such adjustment or override capability is matched with workflow and documentation tools to automatically track all activities by time, user and reasoning.

Given the right analytics, automation tools and workflow features, organizations investing in cloud-based IBP should have measurable targets for streamlined supply chain and fulfillment processes, lower operating costs, and improved customer service and profit. That’s been our experience at Vanguard Software.  Learn more about forecasting accuracy by downloading our whitepaper at

Neal Goffman is the chief sales and marketing officer for Vanguard Software. He is an analytics veteran with more than 20 years of domain experience. Goffman has held strategic leadership roles for organizations including IBM, CIBER and several startups over his career.