Panama hats originated in Ecuador, the koala “bear” is actually a marsupial, and the sago palm is not a palm at all but a type of plant known as a cycad. If you look hard enough, you will find hundreds of things that are similarly misnamed—and one of them would be enterprise resource planning (ERP) systems. Sure, ERP systems have done a great job integrating and automating core business processes, but unless you happen to be a manufacturing company, I would argue that they have fallen short on supporting planning and are probably better renamed as enterprise resource management (ERM). Spreadsheets typically fill the gap in planning—recent research from APQC suggests that 95 percent of organizations use them somewhere in their forecasting, planning, and analysis (FP&A) process. For 39 percent of respondents, spreadsheets are the primary tool, with another 56 percent of companies using them alongside a dedicated budgeting application—simply because the solution is unable to support the type of planning that users need to do on a daily basis. ERM’s endless loops As illustrated in the diagram below, this reliance on spreadsheets typically results in a process that is both long and involves endless loops. Data is extracted for legacy applications (such as ERP systems or enterprise FP&A solutions) and modeled by disparate users in a plethora of loosely connected spreadsheets. After numerous iterations where dimensions and business logic are changed without any record of how, why, or by whom, a version is eventually produced that is considered acceptable to present to senior management. At this point, that version is frozen in time by capturing screenshots of both graphical representations of the data and high-level reports that are combined with further narrative for presentation to senior executives. Inevitably, further analysis is required before a consensus decision can be reached, so planners have to delve back into their spreadsheets to recut new scenarios based on amended assumptions. Finally, once a decision is made, some of the data might find its way back into the legacy systems for reporting actuals against budget. As you can see, the endless loops and disparate spreadsheets compromise the agility that enterprises need today. Since many senior managers have to make decisions using financial information that lacks operational insight, their decisions, by necessity, typically also incorporate a fair amount of guesswork. I recommend the following few steps to simplify the planning process and bring more agility to your organization: 5 steps to improving corporate agility
- Move away from spreadsheets. Using spreadsheets for enterprise planning is laborious and time-consuming, compromising agility at every turn. Instead, link to spreadsheets for reporting and data entry, but do all the modeling in a solution that can cope with the volumes of data and complexity encountered in business today.
- Make the leap to real time. This is essential for getting instant insight into large volumes of transactional data, regardless of the complexity of calculations, the level of granularity, or the dimensionality of the model.
- Insist on a self-managed solution. Many real-time planning solutions were not designed so that users themselves can build and maintain their own models. Using them results in delays as users wait until internal or external expertise is available to amend models and construct new “what-if” scenarios. Because Anaplan uses familiar business syntax, drag-and-drop hierarchies, and has built-in logic for time, versions, and scenarios, users can build and amend models themselves without any technical assistance. That makes it quicker to build and run new scenarios, which is essential for improving corporate agility.
- Give users the detail and flexibility to work the way they want. Anaplan enables business users to build multi-dimensional models to any level of detail, with any number of dimensions, and layer in different views of time (e.g., daily, weekly, monthly, quarterly, and yearly all in the same model). This flexibility means creating different views of the data takes just a few mouse clicks, eliminating the delays that are typically encountered when someone asks for more detail or a different view of the data.
- Enable collaboration. Users should be able to safely and simultaneously collaborate on shared models and deliver the insight required in as quickly as possible.