Overcoming Traditional Forecasting Challenges With Cloud-Based Planning

JS Irick

When it comes to cloud-based financial planning and analysis (FP&A) solutions, most providers choose to advertise based on their analytics capabilities as opposed to their planning strengths. In many cases, this analysis-first branding even extends to their names – the very first thing a user learns about a solution. In my opinion, this focus comes not from a planning weakness, but from three simple truths:

  • It is easier to show compelling analytics demos than planning demos (both in terms of packaged demos and pre-sales custom demos).
  • Analysis processes are relatively similar across customers when compared to planning processes.
  • Analysis is more likely to be white space for customers. Rather than compete with their existing, highly customized planning instance, providers can pitch net-new functionality.

So today, let’s take a look at what cloud FP&A solutions do really well from a planning-specific perspective. In particular, I want to look at three areas where the “Excel-first” philosophy is a detriment to planning as opposed to an advantage.

The occasional-user experience

For the finance user who lives and breathes Excel, the user experience in mature planning solutions is excellent. They’re right in Excel, and users can leverage their years of expertise with formulas, VBA (Excel’s built-in programming language), and spreadsheet design. Additionally, the copy-and-paste functionality enables ad hoc analysis. Simply copy the cells you want, paste them into a new Excel file, and away you go.

But the Excel-based user experience is a challenge for the occasional user (defined as weekly or monthly users). This is made up of two groups: the occasional reader and the occasional writer. The occasional reader is often a manager or executive who needs to be viewing scorecards, dashboards, or key reports. The occasional writer might be a manager making adjustments or someone entering key planning data, such as headcount or sales forecasting.

Occasional users can make up over 60% of an organization’s user base!

Number of queries generated by occasional users

Figure 1. Number of queries generated by occasional users

There are a number of challenges for the occasional user. Where do I go? How do I install the plugin? What do I do? What’s my login? Where’s my report?

For the occasional reader, these problems are generally solved either by emailing reports or using an entirely separate piece of software for dashboard display. For occasional writers, a workaround is usually created, with an administrator collecting the data from each user (or leveraging something like a SharePoint folder). These workarounds increase IT spend, create data latency, and increase security risk.

Cloud planning solutions improve the occasional user’s experience in several ways:

  • No planning or reporting plugin installation
  • Full mobile support
  • Reduced knowledge required for report creation/consumption
  • Increased context awareness for tasks (e.g., drill-down, filtering, etc.)
  • Easier access to reports (favorites, searchable reports, etc.)

Cross-unit collaboration is necessary for true enterprise planning, and the occasional-user experience of cloud planning solutions ensures that your platform is accessible for all users.

Iterative planning

Planning professionals, like all scientists, thrive on iteration (repetition of a process). However, most on-premises planning solutions make this challenging. Each organization has a different strategy for forecast versioning, but in general, they will have a limited number of “working versions” for a given forecast, which leads to a number of challenges.

  • Collisions – When multiple people are working in a given version, running processes can impact each other’s data.
  • Lack of context – What makes forecast_v3 different from forecast_v4? What assumptions are included?
  • Challenge combining forecasts – If different users are forecasting in different versions, it is challenging to combine their data.
  • Collaboration/sharing – How do users self-organize to work on individual parts of the forecast?

To work around these challenges, the forecast team often simply creates their own offline forecast versions – as in the case illustrated below. This defeats security, increases risk, and impedes collaboration.

Competing forecast versions

Figure 2. Competing forecast versions

Each cloud planning solution has different advantages around versioning and iteration, but by and large, they provide a versioning framework that more closely aligns with how users actually plan. For any organization looking at cloud planning, it is critical to understand not only the published planning process but how users actually plan.

Of particular note are solutions that support per-user versioning, which allows users to create their own version. They can edit, modify, and share them among collaborators before publishing the relevant data to an existing version.

Centralized logic

Over time, complex organizational planning processes build up a huge volume of internal forecasting tools – statistical models, customer formulas, unique KPIs, visualizations, external data sources. These tools are incredibly valuable and can help lead to improved forecast accuracy and decreased cycle times. There are also a number of downsides. These tools are typically decentralized and lacking in documentation, which means they are outside of organizational control. They don’t have much error-handling or QA testing and are difficult to reuse or extend.

Modern cloud planning systems greatly reduce the need for this decentralized logic, not through any groundbreaking technology, but through a number of incremental improvements:

  • Improved real-time calculation capabilities allowing formulas to be embedded in the account/measure dimension
  • Batch data processing capabilities enabling allocations, data movement, and data enrichment to be performed immediately on a data update
  • Cross-model reporting removing the need to push/duplicate data
  • Handling of non-financial data, including external data in the financial planning process in a controlled, centralized way
  • Stronger statistical engines removing the need to leverage external statistical tools for business calculations
  • Better filtering/lookups in formulas enabling creation of formulas that filter based on master data and are capable of looking up drivers. The lack of capabilities in this area is a key reason for Excel-driven external reporting.

Once these capabilities are centralized, they can be leveraged across reports and applications. More important, when these calculations need to be updated, they can be modified in one place, and you avoid the risk of legacy reports not being modified. This leads to more capabilities for the business and fewer maintenance risks for IT.

There will always be change-management challenges for any planning-process migration, and there is significant investment and experience required with this decentralized functionality. The improvements listed above allow organizations to approach this discussion from a position of strength, offering improved, maintainable logic.

Conclusion

In many ways, the “analytics first” marketing strategy for cloud-based FP&A solution buries the lede. Cloud planning applications provide a number of huge improvements for planning users and more closely align with the ways organizations actually plan. In this article, we discussed three key areas where cloud solutions are conquering planning challenges. With their rapid development and ability to quickly gather usage data, I expect cloud tools to continue innovating and improving.

To deliver best-in-class analytics, you need to prepare the relevant data first. Join our webinar on July 16 and learn about the latest updates on data preparation and integration in SAP Analytics Cloud

TruQua is an SAP silver partner.


JS Irick

About JS Irick

JS Irick is director of Data Science and Artificial Intelligence at TruQua. He has the best job in the world: working with a talented team to solve the toughest business challenges. JS is an internationally recognized speaker on the topics of machine learning, enterprise planning, SAP S/4HANA, and software development. At TruQua, JS has built best practices for SAP software implementations in the areas of SAP HANA, SAP S/4HANA reporting, and SAP S/4HANA customization.