A beginner's guide to the business maturity model framework

Business Process Management

Maturity models are representations of capability for continuous improvement in a particular discipline. Here's an example of how to implement a maturity model for your SaaS organization.

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Vendr Team
Published on
December 2, 2022
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A maturity model can be a great tool to help you assess the effectiveness of a current group or individual. Maturity models describe known states of being at various levels for given disciplines. Likewise, they provide examples companies can use to implement process improvement.

In other words, a maturity model is a tool for a business to actualize, grow, and reach its potential.

What is a maturity model?

Maturity models are simplified representations of capability for continuous improvement in a particular discipline.

The model judges how well your company or system improves itself from a given state. It assesses a company’s maturity level in the discipline's quality or resources.

In general, maturity models consider qualitative information when examining people, culture, processes, structures, objects, and technology.

For instance, in a data technology maturity model, we identify the maturity levels around a company’s data use. Each maturity model level describes a business's growth when it uses data in a specific way.


Why maturity models are essential for business

Overall, using a maturity model as a foundation for improving practices, performance, and processes provides your company with the ability to

Benchmark internal performance.

Benchmarking helps you determine where the organization is in its improvement journey. You can then set clear objectives for future investments in performance improvement.

Catalyze performance improvement.

The model can produce action plans to close performance gaps and improve maturity, as it reflects industry best practices.

Create and evolve a common language.

Maturity models help ‘knowledge domains,’ like data science grow into disciplines. Then, this common language can translate into consistent, repeatable, and predictable performance over time.

In short, a business maturity model tells you where you can improve in a given area. It can benefit companies pushing for digital transformations because the models help you identify problem areas to reach your business goals.

Maturity models can also tell you what steps to take next when improving your maturity level, i.e. the business ‘maturity curve.’

This improvement, in turn, helps your business reach new maturity levels. So the more significant the maturity, the greater the chances that events or failures lead to improvements in your organization.

How are maturity models used for improving businesses?

Businesses use maturity assessment models to learn about themselves. Models help companies learn their maturity level. Then, they inform them how to improve by asking questions and developing action plans.

Maturity models also help organizations make better investment decisions. Maturity models can generalize progress estimates by determining what resources it will take to ascend to the next level.

Companies use maturity curve models to generate timing estimates. An example use is determining how long it takes the IT department to implement new SaaS products.

Then, using finished work as a reference, the model helps structure generalizations. For instance, it measures projects completed and how long it took to complete each project.

Types of maturity models

One of the first models developed is the business capability maturity model (CMM). The Software Engineering Institute (SEI) created this model to measure software development processes.

Next came the capability maturity model integrated (CMMI), which developed maturity models like project management maturity models and others.

CMM provided these five core model levels, which most other models could use as a foundation to measure business growth:

  1. Initial: Beginner stage
  2. Repeatable: Proficient stage
  3. Defined: Savvy stage
  4. Managed: Expert stage
  5. Optimizing: Mastery stage

The most popular model is the business process maturity model (BPMM). It’s popular because of its ease of adoption, ease of use, and ability to boost productivity and lower costs.

This model has a few variations. They include the agile ISO maturity model (AIMM), which uses agile business process management tools to attain ISO-level standards. Another variation is the business process management capability framework (BPM-CF).

In all, there are nine known models to measure maturity in business:

  1. Business process management capability framework (BPM-CF)
  2. Business process maturity model (BPMM-FIS)
  3. Business process maturity model (BPMM-HR)
  4. Business process maturity model (BPMM-OMG)
  5. Business process orientation maturity framework (BPO-MF)
  6. Business process orientation maturity model (BPO-MM)
  7. Process and enterprise maturity model (PEMM)
  8. Process management maturity assessment (PMMA)
  9. Value-based process maturity model (vPMM)

Which business process maturity model is the best?

Most academic literature references the Business Process Orientation Maturity Model and the Business Process Management Capability Framework. However, that doesn’t necessarily mean they’re the best or most popular in practice.

Researchers relied on academic literature for data since the use of existing BPM maturity models is limited.

Researchers think it is uncommon to put BPMMs to use in practice, and that they are mainly designed for descriptive purposes. So, no single model is widely applied in practice. There is no conclusive evidence that one BPMM is the best.


Maturity model example for SaaS

Software companies might use many maturity models to measure their business processes. For instance, SaaS firms may need to measure how effectively they manage their data organization.

Data maturity is the degree to which a company uses its data, often measured in stages. It’s a partnership between IT and the business to expedite using data to make a decision.

For businesses, the vision of a maturity model looks like analyzing data and looking for insights. It asks questions like, “how can we leverage data to discover new insights and innovations?”

In other words, a company’s data maturity management level indicates its ability to focus on turning ideas into reality.

How do you measure data maturity?

According to CIO, there are “Four Stages of the Data Maturity Model.” In another article, Scott Castle of Towards Data Science adds the fifth stage.

We’ve compiled all five levels to measure your data maturity here. Then, you can apply these models to other technological disciplines within your organization.


Businesses take a manual approach to compile reports from various systems to standardize reporting. Their challenges include needing more data and app integration, developing ad-hoc reports, and distrusting those reports.


Organizations begin tracking key performance metrics and indications (KPIs). Then, they can interrogate the data’s quality. In this stage, they may start to understand limitations like having many databases, incomplete data warehouses, or limited app integration.

Challenges may also include lacking executive support or not knowing how to handle unstructured data.


Companies now use data to make crucial decisions for key ambitions. This improves the business-IT partnership up by breaking down organizational and data silos.

Challenges include integrating all applications and data sources for better on-demand service and using unique data within the business.


Business and IT partnerships reach the ultimate stage of data maturity, working together as a cohesive unit. IT integrates apps and data sources and installs an advanced analytics program. The organization identifies business processes to embed analytics. Their challenges include scaling the data strategy while reducing costs and maintaining competitive advantages.


Data scientists use machine learning, statistical technologies, and predictive capabilities to optimize operations at scale. Organizational challenges can include relying on data scientists and predictive technologies to deliver value. Another challenge is the investment of time and money into these resources.

How to use the 5-stage data maturity model for organizational impact

Data must be deeply ingrained into making decisions. But what do you do if you’re behind the competitive curve, and how can you “level up” quickly?

Castle writes, “Significant investments in machine learning may or may not be what’s right for your firm. A good hard look at the maturity curve is the best way to a path forward.”

Key questions to determine your maturity level

Determining your maturity level requires an honest self-assessment to create a realistic view of your current state.

The five-stage data maturity model can help you assess your company's level of maturity by asking important questions.

Here are some examples:

  • Do you have different platforms reporting on other business functions?
  • Is your system of record siloed across different divisions, or is reporting integrated across your various business tools?
  • What percentage of data does your business incorporate into a single source of truth?
  • How well are you moving toward your goal?
  • Can you blend model data with raw data from many sources?
  • Does the data blending occur before or after it arrives at the warehouse?
  • Does your data comprise all customer journey phases, or does it favor specific areas?
  • How many within your company have access to data, and at what levels?
  • Does your firm have model management capabilities?
  • Have you deployed machine learning systems, and are they used in your products or analytics?
  • Does your analytics workflow include machine learning models?

After answering the questions, you can chart a path to achieving the next level. You can start this process by identifying the gaps in skills, knowledge, tools, and practices that can get your business there.

How to follow a maturity model

Your company must go through the maturity model step-by-step. Otherwise, it might bypass some fundamental capabilities, potentially limiting the organization from achieving results from advanced analytics.

Castle summarizes:

“Firms that follow this curve are better positioned for long-term competitive advantage. Building this connective tissue that lets an entity operationalize insights for real business value.”

How Vendr helps your organization implement growth-oriented best practices

Regardless of what business process or discipline your company aims to improve through a maturity model framework, Vendr can help.

Vendr offers a complete SaaS management solution that organizes and focuses your technology stack.

With centralized visibility and control, Vendr helps the whole organization become more efficient with its software stack.

  • A system of record to replace your spreadsheet
  • Improved SaaS operations and SaaS spend optimization
  • IT automation to save you time and money
  • API integration

Learn about how a vendor management system can improve your overall ITAM practice. Discover the advantages of automating software management with our free guide.


Vendr Team
Vendr's team of SaaS and negotiation experts provide their curated insights into the latest trends in software, tool capabilities, and modern procurement strategies.

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