Our Journey to Low-Code Planning - Chapter 2

How we landed on a platform-based approach...

Over the last year and a half, we tried out many EPM software solutions in search of the latest and greatest, something that would provide maximum value to current and future clients. 

We looked at everything from tried-and-true options like Adaptive and Planful to new Anaplan competitors like Pigment to upstarts like Causal and Pigment. 

Based on all our research, we determined that there was a need for a more open platform-based approach to planning - an approach that is more accessible, collaborative, and cost-effective. 

Four observations that led to this conclusion: 

EPM software is getting more expensive and providing less value. 

Everything is getting more expensive, but the rate of cost increases for EPM software was concerning to us and to our clients. In some cases, we saw 50%+ hikes on renewal. Turns out there is no rent control SaaS, and EPM software tends to have a high degree of lock-in. 

Pricing has also been getting more complex, with platform fees, storage fees, use case-based pricing, and even subjective value-based pricing. Add-ons are also becoming more common. In one case, 25%+ of the subscription cost was coming from unused add-ons. We also made note of customers paying for specialized apps on top of their EPM subscription. 

This was a theme across all the top EPM solutions. All the above speaks to the value of effective planning, but too much of the value was going to software providers, instead of to customers. These pricing trends were the main reason our clients started coming to us looking for alternatives. 

The EPM software buying experience remains opaque for customers. 

While other enterprise software solutions have started adopting more customer-friendly buying processes with month-to-month commitments, free trials, and transparent pricing, the majority of EPM software is still sold in traditional SaaS fashion, with long sales cycles, multi-year commitments, upfront payments, and demos that do not represent reality. With AEs, SDRs, SCs, and consultants all involved, the process gets expensive very quickly, and that cost is borne by the customer. 

In addition to pricing, product capabilities are also opaque. EPM expertise tends to be very specialized, and it is rare for the folks selling to understand the product in practice, and even more rare for them to understand the competition in practice as well. It was a challenge for us to be objective representing our clients while also learning new solutions. Generally, we found that it was close to impossible for clients to fully understand product capabilities without taking a leap of faith. 

EPM software is often adding to siloing problems, not solving them. 

While historically EPM solutions could become a unified source of truth, this outcome is increasingly rare. Now in many cases, EPM software is just another data source for a data lake or data warehouse. 

Due to data volume, license costs, increasing importance of unstructured data (text, audio, images, etc.), and specialization of software, most EPM solutions are trending toward being ‘FP&A solutions’ as opposed to planning platforms, becoming another functional silo instead of a silo-breaker. 

In addition to adding a data silo, EPM software also created another collaboration silo. Lately it seems like every function has its own software and its own operations/systems resources. With too many solutions competing for attention, leaders and operators are defaulting back to Google or Microsoft for collaboration, common ground for everyone. 

EPM software is less AI-ready. 

With the AI boom, our bet is that EPM software providers will not be able to keep up with the bigger players in terms of AI capabilities. The analysis needed for FP&A is not different from the analysis needed for sales, operations, BI, data science, etc., and AI advancements will move much faster on platforms than specialized solutions. 

EPM software is also not set up to handle unstructured data, which will be increasingly relevant for planning with generative AI. EPM solutions will release chatbots and AI features, but without all the data and the openness to build custom AI agents, EPM solutions will lag behind platforms. 

Landing on Platform Planning 

Why platform planning? 

Our belief is that planning should be collaborative, data-driven, continuous, and efficient. As we thought about these principles and considered the above, we concluded that for many organizations: 

1. Planning today doesn’t necessarily need a specialized tool or specialized capabilities. Instead, planning needs to be based on common data, a common language, and common tools to tell a business performance story that everyone will understand. 
2. Planning should be highly flexible and customized to each organization’s specific needs, especially in times of uncertainty. 
3. The last thing they need is more software subscriptions. Thus, we are not in the business of selling software with this approach, only the same tech-enabled services we have always provided, on a platform that most organizations already have. 

A platform-based approach will not be right for everyone, and many organizations will still have success with any of the EPM software providers. With that said, technology is cyclical and platform-based approaches are a natural balance to best-of-breed approaches. The time is ripe for the pendulum to swing the other direction. 

Why Microsoft? 

While Microsoft is not marketed as an EPM solution (it had a failed EPM endeavor called Performance Point that was shuttered in 2009), it checked all the boxes we were looking for: 

• It is cost-effective, even for small businesses. Pricing is simple and self-serve with free trials and month-to-month commitments. 

• It is a true platform (in fact, a platform of platforms) with a full productivity platform, data and analytics platform, product-building platform, and interoperability with any other system. 

• It is AI-ready, as Microsoft is leading the way on enterprise AI with Copilot, has a data-centric platform, and has already figured out things like user access with chatbots. 

This is not a novel idea, as many others have already built planning apps on Microsoft with Power BI writeback, and Microsoft themselves use it for planning. We have confirmed that the building blocks are all there, they just need to be assembled in the right way. 

Why now? 

If this approach is so obvious, why aren’t more people doing it now? There are two major recent unlocks that make Microsoft even more compelling for planning, instead of the ‘Excel hell’ that everyone has been trying to escape. 

First is the release of Fabric, which can directly connect to both Power BI and Excel, providing a scalable platform for both structured and unstructured data in a business-accessible format, and with pricing that is accessible from SMB to Fortune 500. 

Second is the release of Copilot (and generative AI overall), which is dramatically lowering the barrier to entry for any kind of technical execution. Now instead of spending years learning DAX or Power FX, any Excel-savvy FP&A practitioner can be a dual threat with AI, proficient both in business and technology from building apps to maintaining data warehouses. 

What’s next? 

As we did with Anaplan and all the other solutions we explored, we have built out an end-to-end FP&A solution covering all the basics first: P&L modeling with revenue planning, vendor-level expense planning, and employee-level headcount planning, balance sheet and cash flow modeling, management and budget owner reporting, and forecast process management. 

This solution has proven out the platform approach for us and will serve as an accelerator for deployment. We will then put this approach into play, continuing to improve it while also pushing the envelope on new ways of working with automation and AI, and delving into other planning use cases such as demand planning and incentive compensation. 

We are excited to share more details starting next week. Shoot us a note if you are interested in a demo! 

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