BD #27 - An Analytics Maturity Model Template to Drive Change
Adapt this 5-stage maturity model to grow you data and analytics capabilities.
Results are in - last week, I asked what kinds of content you would like to see more of and a whopping 44% of the votes called for systems and templates for running data teams.
So here we are - this week, I’ll introduce the high-level maturity model I teach organisations and talk through how to use it. I’ll also touch on the dangers of maturity models and following them blindly!
A 5-Stage Analytics Maturity Model
The ability to harness the power of data and analytics is a huge competitive advantage for most organisations looking to make sense of the turbulent markets and ever-expanding tech landscape.
But how do you move from being data-curious to an analytical powerhouse? In this issue, we'll dive into a five-step maturity model for data and analytics capabilities and try to provide some actionable advice to transform an organisation's approach to data-driven decision-making.
This model is heavily inspired by Competing on Analytics by Davenport and Harris. Well worth a read - something I often share with non-technical leaders in a business to learn more about the advantages of data and analytics.
Step 0: Unaware, Don’t Care
In the "Unaware, Don't Care" stage, organisations are oblivious to the value of data and analytics.
In this stage, the organisation lacks awareness of the potential benefits of data-driven decision-making and may be resistant to change. Leadership may be firmly entrenched in traditional methods of decision-making, relying on experience and intuition rather than data and analytics.
The organisation is not leveraging data and analytics capabilities to drive insights or enhance decision-making processes. The risks of staying in this stage include falling behind competitors, missing growth opportunities, and struggling to adapt to market changes.
Be wary of going in, guns-blazing, telling successful businesses that they need to completely change their decision-making processes!
To move forward, the organisation needs to recognise the potential benefits of analytics and commit to exploring its possibilities. By acknowledging the value of data-driven insights, the organisation can progress to Step 1 of the maturity model and start building its data and analytics capabilities, beginning its journey to becoming a data-driven organisation that thrives in today's competitive landscape.
Step 1: Awareness and Uncertainty
At this stage, the organisation recognises the importance of data and analytics but is just starting to dip its toes in the water. The key here is to begin understanding the potential benefits and applications of analytics.
You want to find and empower champions to explore the Art of the Possible and start to identify some easy wins to get the business enthused.
Educating the team and wider stakeholders on the basics of data and analytics
Identifying opportunities where data-driven decision-making could have a significant impact
Establishing a data-driven culture by encouraging curiosity and openness to experimentation with low-risk bets
Step 2: Localised Analytics
Now that the groundwork has been laid, it's time to start applying analytics in specific areas of the organisation. There will be pockets of activity, with some areas well ahead of others. Remember, organisations will move through this model heterogeneously, and you may take some steps back to move everyone forward.
In this stage, you'll see some success stories as teams implement small-scale analytical initiatives. You’ll start to hear murmurings of wanting a central data repository, automation for some cross-cutting data workflows, and shared reporting.
To move forward:
Encourage teams to share their experiences and learnings from analytical projects (this is a people thing more than a tech thing)
Begin to develop internal analytical talent by providing training and resources
Identify areas where localised analytics initiatives could be scaled up or replicated across the organisation
Step 3: Organisational Aspirations
In this stage, the organisation has seen the value of analytics and is ready to invest in building a more robust analytics infrastructure. Some significant wins have been realised, and senior executives are starting to want more. You'll need to develop a strategic plan to scale your analytics capabilities.
It’s at this point many organisations get stuck and/or lost. They either take on something too big - slowing progress and frustrating the early adopters into leaving - or they get the wrong sort of help and end up spending a lot of resources building the wrong things.
Focus on the following:
Gaining and maintaining executive sponsorship for analytics initiatives
Identifying and addressing gaps in data quality, availability, and technology - identify tools that raise the bar across the whole organisation
Developing a roadmap for building and scaling analytics skills and resources
Step 4: Analytics-Driven Companies
At this stage, an organisation is well on its way to becoming an analytical powerhouse. The organisation is committed to building world-class analytical capabilities and has a plan to achieve this goal. Analytics and data are at the heart of many core processes, and the general understanding of data and analytics is growing across all functions.
Foster a culture of experimentation and continuous learning - increase the speed of iteration and knowledge sharing
Realign analysts and information workers to maximise their impact on strategic issues
Manage the necessary cultural and organisational changes, ensuring widespread executive sponsorship and support is maintained (can you tie this into people’s core performance metrics)
Step 5: Analytical Leaders
The organisation has reached the pinnacle of analytical maturity. Analytics is a driving force behind the organisation’s competitive advantage, and it is maximising returns on the investment in data-driven decision-making.
Many of the largest tech companies in the world have analytics at their core. This might not be a realistic destination for many organisations - that’s fine. It takes a huge investment to get here and maintain that edge.
There’s little advice to give here, but common activities by these sorts of organisations include:
Maintain an unwavering commitment to analytics, ensuring it remains a top priority for executives and decision-makers
Continuously monitor the external environment and remain vigilant for signs of change
Stay ahead of the curve by exploring new applications, techniques, and technologies to enhance your analytical capabilities further.
Things to Avoid
As you progress along this roadmap, you may encounter challenges and potential pitfalls. Keep these guidelines in mind to stay on track:
Don't focus solely on technology; building a solid analytical culture and developing talent is more important, in my opinion. Get the people right, and the tech will take care of itself
Avoid trying to do everything at once; prioritise projects with the most significant potential impact on the organisation's competitive advantage. I also like to focus on “most-likely wins” in the earliest stages
Watch for signs of complacency, self-serving analytics, or manipulation, and enforce a culture of objectivity and integrity
A word of warning
While maturity models can provide valuable insights and guidance for organisations looking to improve their capabilities, blindly following a model developed externally to the organisation can be fraught with danger. Maturity models are often non-sensical outside of the specific context, culture, and goals of the organisation that created them, which means that they may not be directly applicable to your organisation's unique circumstances. Think curse of knowledge etc.
One danger of blindly following a maturity model is that it may lead the organisation to invest resources in initiatives that aren’t well aligned with strategic objectives. This can result in wasted time, effort, and other resources, as well as missed opportunities.
Additionally, maturity models can create a false sense of security, leading organisations to believe they have a foolproof roadmap to success. This can result in complacency and resistance to change, as employees become overly focused on ticking boxes and adhering to the model rather than remaining agile and adaptive in the face of new challenges and opportunities.
It is for this reason that this model is so high-level and vague. When I deploy this to a new organisation, I spend a lot of time tailoring and tweaking it so that it’s right for them.
Organisations should approach maturity models as a source of inspiration and guidance rather than a one-size-fits-all solution. It's essential to critically assess the relevance of the model to your organisation and adapt it as necessary to better align with your specific context, goals, and challenges.
Ultimately, the key to success lies in striking a balance between learning from best practices and maintaining the flexibility and creativity to forge your own path.
Transforming your organisation into an analytical powerhouse may seem daunting. Still, by following this five-step maturity model and being honest about where you are, you'll be well on your way to harnessing the full potential of data and analytics. Remember that becoming an analytical organisation is an ongoing journey, so stay curious.
All the best,
When you're ready, there are a few ways I can help you or your organisation: