An actionable guide for small and medium-sized businesses on how to advance your data maturity.


For any business, it’s vital to understand not only the importance of using data in the modern world, but also how this data can be shaped to fit in with your business model.

There’s no doubt about it, data is important. For small and medium-sized businesses (SMBs), data use can be the difference between sinking or swimming, especially in times of economic hardship. With access to high-quality data and analytics, business leaders are empowered to make informed decisions, based on trusted insights.

Whether it’s used to monitor and optimise your operations, or to locate possible sources of error or even to identify needless expenses, the business value drivers for the application of data are endless.

After all, data is knowledge and knowledge is, ultimately, power. That’s why we’ve designed our data and analytics maturity framework for SMBs, to help business leaders to understand their current level of maturity, so they can take actionable steps to becoming a more data-driven organisation.

Our framework is comprised of six categories:

  • Strategy
  • Process
  • Data
  • Platforms
  • Analysis
  • Culture and Skills
How Data-Driven is your organisation

This guide is focused on the data aspect of our maturity framework, providing your business with expert guidance on the following dimensions:

  1. Data Variety
  2. Data Availability
  3. Data Cleansing and Governance

To start analysing data efficiently and effectively, the best place to start is by focusing on the business challenges and then identifying the data can help inform decisions in those areas. To ensure your data is in a state to be used correctly, you may face some challenges. 

Are you finding it difficult to transfer analysis from structured to semi-structured and unstructured data sets? Is data availability and access something you feel like you’re struggling with? Are you having some trouble handling and processing your data, or even finding it difficult to convince business partners of the importance of business data?

No matter your data worries, we’ve produced a series of resources to help you create a smarter, more data-driven business.

1. Data Variety

Data can come in all shapes and sizes, with different sources of data providing different insights into each aspect of your business.

For example, in recent years social media has gone from a useful source of direct consumer communication to an essential platform, responsible for the success of thousands of marketing campaigns and a huge source of consumer data. Companies have built themselves from the ground up through social media usage, giving them access to a wide variety of data beyond structured internal sources.

Data can be incredibly diverse, but with diversity comes complexity. Many companies are quite comfortable utilising structured data, but with additional data sources coming from social media, surveys, images, audio and more, businesses have to become comfortable analysing data from semi-structured and unstructured sources.

Making smarter analytical decisions is the key to staying competitive, and harnessing the power of structured, semi-structured and unstructured data helps to power key decision making to improve business processes, reduce costs and maximise value.

All businesses deal with structured data and that is definitely the place to start when it comes to handling your data. However, semi structured and unstructured data use is also vital for modern businesses, no matter of size or data maturity stage.

In fact, most of the data present in our world is unstructured, coming in forms such as images, audio or video as well as PDFs or invoices. Without the ability to harness this enormous amount of information, SMBs may be missing out on key information to form their decision making. Working with semi-structured and unstructured data may sound like a tough task, but in the end, the possible growing pains are vastly outweighed by the huge benefits these data sets can bring to your business.

Sometimes, being a smaller organisation stepping-out into the world of data can be a huge advantage, especially when you have expert guidance. If your business is quite early in its data and analytics maturity journey, you’re in a perfect place to plan for future scale. It’s also much easier to get into great data handling practices, because there are fewer data handling habits that you may need to break first.

2. Data Availability

Before your business can start generating insight from your data, the data first needs to be available for analysis! Data availability can mean different things to different businesses who are at different stages of data maturity. For example, a business that is just starting out its journey to data and analytics maturity could start by identifying, documenting and sharing their data efficiently and appropriately for analysis.

This type of change can come in a few ways, but one of the first ways to create efficiency in data availability is to introduce and train staff in more efficient data tools beyond Microsoft Excel to improve data visualization and data prep.

However, as organisations grow, data availability becomes less about methods of visualisation and more about the automation of the data preparation process and the widespread accessibility of data for departments across the company. This can be achieved by ensuring the data is extracted and prepared in a consistent and automated manner for analysts to consume.

Businesses should also implement resilient mechanisms for accessing, minimising the possibility of data becoming unavailable for analytics.

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However, one major problem that businesses transitioning to higher stages of data and analytics maturity run into is creating mechanisms for sharing and collaborating between departments. When starting their journey towards greater maturity, companies often find themselves storing their data in departmental data silos due to a lack of communication between departments.

This can create a problem if analysts require access to information stored in different silos to gain relevant data, as this can slow down the entire data analysis process and make data communication between different departments of a company far harder than it needs to be. Having different departments prepping their own versions of data and not communicating with each other can impact data reliability as there may be inconsistencies between sets of data that purport to reflect the same information.

It’s also simply a waste of resources to have to transfer data frequently between different silos. Breaking down these data silos and appointing data owners to enforce governance controls are key aspects to building a smarter, more efficient common pool of data and analysis. Although this seems quite difficult for businesses who have entrenched data silos into their data process, breaking down these silos can be easier than you may think, with the necessary governance and appropriate use of data management platforms.

3. Data Cleansing and Governance

With great data comes great responsibility. As your data sources, variety and availability increase, so does the task of managing and processing all that new data. Data governance helps to ensure the integrity of your data through conserved processes that give instructions on exactly how to manage data assets within your organisation. By setting in place rules for the handling, storing and maintaining of data, SMBs can set accountability for the quality of their overall data sets.

Data, first and foremost, should be used to drive decision making amongst senior members in the company. To do this, data must be processed and maintained to the highest possible quality through the rules set down by data governance and data cleansing.

Data cleansing is important because, in most if not all cases, bad data is worse than no data. Data cleansing allows for bad data such as corrupted files, incomplete data sets or duplicate data to be removed from or fixed within the overall data set. This is especially vital during the movement or combination of data sources, as there are many more chances for data to become mislabelled or unreliable.

A frequent barrier often encountered is that the data quality is sufficient for the data owner’s own purposes, so there is not an incentive to improve it for organisation-wide analytics. Often, this can only be overcome through robust senior data sponsorship coupled with regular data quality reports highlighting where the data is not up to standard.

One of the greatest difficulties surrounding incorrect data is that in addition to making analytical outcomes or created algorithms unreliable, it’s not immediately obvious that the data is the thing that’s flawed. This can waste time and resources by looking for problems in the wrong places and hinder the overall adoption of the data strategy due to a degradation of trust in the analytics. However, with proper data cleansing and governance this can be much easier to avoid.

Sometimes, even with the looming threat of bad and absent data, the trickiest aspect of data and analytics isn’t even the data itself: it’s convincing business partners that data and analytics governance is of greater importance to business than just IT. As a CEO or member of senior management, it can be difficult to see how and why data governance is so vital to the company as a whole. Having a clear roadmap, with actionable steps for your data governance journey cleanly laid out, is one of the best ways to introduce and explain exactly how your company can transition to a consistent, efficient method of data governance and cleansing.


The three dimensions we’ve discussed in this guide can help your business to progress through each level of data maturity, with certainty and confidence.

Regardless of the current level of maturity of your organisation, and whatever your own personal level of data expertise, our data and analytics maturity guides on strategy, process, platforms, analysis and culture & skills, are here to help you to become more data-driven.

To learn more about the different categories of our data and analytics maturity, check-out our framework or contact us so we can learn more about what your business needs to maximise the value from your data.

The Data-Driven SMB

An actionable guide for small and medium-sized businesses, on how to become more data-driven in an increasingly digitalised economy.

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