Decision Engine Software Billing Models


This is the final article in a series of three, focused on the commercial aspects of decision engine software:

By the end of the series, the reader will have a better idea of the various types of commercial models that are available from decision engine software vendors. Hopefully, the information can be used to make more informed decisions.

Timothy Noah summed up how important billing is as an aspect of modern life:

“In removing the friction involved in paying bills, electronic billing has substantially increased the friction involved in not paying them.”

What is a Software Billing Model?

Deloitte has created an excellent report on pricing models, which will be referenced in this article.

Within this report, they provide the sage advice: ”don’t confuse pricing models with billing models.”

“Pricing models are not to be confused with billing models (the timing of when money exchanges hands), pricing tactics (manoeuvres to impact customer acquisition or adoption) or pricing itself (the actual monetary value). The relationship between pricing and billing is often neglected in the literature. Authors frequently cite “pay-as-you-go” and consumption-based pricing interchangeably, which can be misleading and unhelpful. In fact, we see pay-as-you-go as a billing model that can be applied to almost any pricing model, rather than a pricing model itself.

Regardless of which pricing model a company uses, we think it is helpful to bucket billing models into the following three categories:

3 Categories of Billing Models

  • No commit, pay in arrears – customers send money at the end of each period (usually monthly) based on actual usage. This is the purest form of pay-as-you-go and likely how you pay for your gas and electricity.
  • Commit and pay in advance – customers pay up-front for the year ahead. This is the most common billing model in the B2B enterprise software world e.g., SAP, Oracle.
  • Commit and spread payments – customers commit to an agreed amount of spend but spread the payments over the duration of the contract e.g., equal monthly instalments. This is a variant of commit and pay in advance but attracts customers with less cashflow.”

Deloitte concludes:

“Our clients gave lots of feedback on this topic in our interviews, hence why we’ve clarified this terminology upfront. Billing clearly represents another powerful weapon in the armoury for tech companies to maximise value for themselves and their customers.”

Client Billing Models Feedback

Deloitte undertook detailed qualitative research on pricing and billing models and the top three ‘takeaways’ they identified are:

“Takeaway #1 – Clients don’t love pay-as-you-go billing

It became clear from the get-go that we needed to distinguish between pricing models and billing models. >90% of clients fed back that they dislike receiving an invoice at the end of each month based on actual usage. This finding is surprising given this is how IaaS providers bill their customers today. Monthly billing can apply to any pricing model; therefore we devote our first takeaway to billing model preferences. In short – clients prefer some form of spend commitment. Key billing model feedback:

  • Predictability – making software spend predictable was arguably the top decision driver for our clients. Clients regularly fed back that they “hate bill shocks” and that, given they have annual budgets, up-front clarity on costs for the year ahead was critical
  • Billing model optionality – some clients don’t mind paying for software lump sum for the year ahead while others value the ability to delay or spread payments (and may be willing to pay a premium for this). Billing model preferences varied depending on client industry, accounting rules, or cashflow situation.
  • Administration – more frequent billing (particularly when based on consumption) adds administrative overhead. The cloud billing market is improving, but for now clients fed back that they prefer to pay lump-sum or spread payments quarterly or biannually
  • Alignment with adoption – regardless of billing model, clients value close alignment between payment timing and product adoption. If a product takes six months to implement and a further six months to reach usage capacity, clients would like to see vendors align payment terms to this ramp-up

Takeaway #2 – Clients are split on the per-user vs. consumption debate

Despite the trend toward consumption, clients had mixed reactions to this model and tended to favour per-user pricing for large enterprise-wide purchases e.g., ERP, CRM, or collaboration software. They also fed back that there is a time and place for consumption, but certain conditions had to be met. Key pricing model feedback:

  • Simplicity – pricing models need to be clear and simple in terms of how the software is priced, what features are included and how new product innovations are added. If it requires hundreds of pages of documentation and a team of lawyers to explain, it’s probably too complicated
  • Mixed reaction to consumption – some clients were massively against it. Others favoured the concept. While clients value its close alignment to value and partnership incentives, often this was outweighed by the lack of predictability, budgeting, and control. Clients spoke of strong guardrails needing to be in place for this model to be palatable – “tell me early when I am looking like I might breach my allowance, not after the fact”
  • Value metric – for consumption-based pricing to work, clients spoke of the need for an appropriate transaction meter that is easily measurable, aligned to value and does not disincentivise desired behaviours (“taxi meter effect”)
  • Per-user is ok but can improve – clients regularly cited per-user pricing as the “simplest” and “most predictable.” However, several challenges kept surfacing that clients would like to see resolved, namely – lack of consideration given to seasonal usage, active users, employee attrition, and user ‘type’ (e.g., contractors). This is only going to become more important as workforces become increasingly all-inclusive, boundaryless ecosystems with all types of workers (including contingent workers and part-time employees) being integral to business
  • Type of software matters – generally speaking, clients expected to pay per-user for large enterprise software that is used by every employee in the company (e.g., Microsoft 365) and consumption-based pricing for more boutique, industry-specific or data/analytics-based solutions e.g., Snowflake

Takeaway #3 – The importance of partnership, subscription management and telemetry

So, clients gave us great insights into what really matters to them when choosing software. Turns out there are some other key factors besides pricing that can make or break a decision. Here’s what else we found from our interviews:

  • Strategic partnerships – clients shared that they like to form a small number of highly strategic partnerships with SaaS vendors who are central to their digital transformation journey (often manifesting in the form of an “enterprise licensing agreement”). Clients highlighted that they “want their strategic vendors to succeed” and are “willing to pay fair price so that the vendor can further innovate their products.” In return, clients said they were keen and willing to reciprocate in creative ways e.g., speak at vendor conferences or investor presentations.
  • Subscription management – agnostic of pricing model, almost all clients wanted their vendors to better help them manage their subscriptions. Clients want transparency in the process with vendors proactively helping them manage swaps and true-ups/true-downs(especially in a recessionary environment).
  • Telemetry – clients want their software vendors to enable them with live usage insights. Some clients fed back that this in turn could lead to follow-on monetisable services from SaaS vendors in the form of proactive recommendations based on these usage insights. “Give me a live dashboard that shows me how we are using your product, and I don’t just mean how many people have logged in” – Government CIO”

3 CIOs Summaries and Predictions

CIOs hate surprises. Software pricing needs to be simple and predictable

The CIO of Deloitte Americas summarises with the opinion:

“CIOs have annual budgets. While per-user pricing does have issues (that I don’t think are insurmountable), it is simple and predictable. A budget increase driven by growth in our organisation is more readily understood and aligns with metrics that people easily understand. It also enables easy comparison between vendors e.g., we pay $100 per employee for vendor X and $80 per employee for vendor Y – does this feel about right based on the value we receive.

At the same time, it’s clear that consumption based pricing makes sense in some areas. Software providers have a long way to go to remove the black art in how they price their product, provide real-time easy-to-understand usage metrics, and establish appropriate guardrails to mitigate the risk of bill shock that comes with this model.

I need to be convinced that providers can design a consumption-based pricing approach that is predictable and simple to understand, and clearly demonstrates the relationship between consumption and value realisation. Currently, this model is a niche for us. We are watching to see how this space evolves.”

When it comes to software pricing models, there’s no one size-fits-all approach

Another CIO adds:

“Pricing models should be tailored to fit the unique needs and usage patterns of each product. For software being used across an entire organization, per-user pricing is typically the way to go. However, specialised technology that’s only used by a small

group of employees, such as engineering or supply chain, is better suited for consumption-based pricing. That being said, I challenge vendors to consider supporting multiple pricing models and giving customers a choice. The needs of start-up and mid-market customers are vastly different from those of Fortune 500 organisations.

Given the variety of licensing options, it is my experience that enterprise agreements work well where the relationship is predicated on a win-win partnership strategy. Also, when cash flow is not a challenge, I am willing to pre-pay. But, of course, I would expect a discount from the vendor for doing so. For consumption-based products, I prefer pay-as-you-go billing, but I want real-time visibility to my consumption usage with the ability to influence it.

Lastly, I believe vendors should put more skin in the game, be business outcome driven, and provide flexibility in the software product mix as every company and industry evolves through mergers and acquisitions, market cycles, and business transformations.”

What is your organisation willing to pay for this business outcome?

A third CIO predicts:

“The software market will move more toward value orientated customer benefit pricing. The pricing models of providers will align to the things that really matter. It will be a win-win for customers and technology vendors.

From a billing model perspective, I prefer multiyear contracts with lock-in on price increases. “Relationship pricing” was key to this – large global vendors can price and bundle their services and products under one single enterprise scheme for complex global consumers. It forces them to act as “one company” and not let their customers experience their fractured organisational structures and sales teams.”


This is the final article in a series of three focused on the commercial aspects of Decision Engine software.

ADEPT Decisions Decision Engine software billing model has always been based on transparency and honesty.

Clients pay a once-off, fixed price software set-up fee, based on their detailed requirements. The fee is billed only when multiple milestones are achieved.

Once live, clients are billed in arrears on a monthly basis, based on the volume of applications or accounts that are processed.

This straightforward approach enables accurate budgeting and a true partnership with the client as their business and volumes grow.

About the Author

Stephen John Leonard is the founder of  ADEPT Decisions and has held a wide range of roles in the banking and credit risk industry since 1985.

About ADEPT Decisions

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