Following a recent AWS survey showing that data-driven SMBs who also adopt AI more quickly and make better use of it are financially outperforming their peers, we look at ways your business could do the same.

The Key Findings Of The Report 

A recent study by S&P Market Intelligence, commissioned by Amazon Web Services (AWS), found that SMBs who prioritise data (i.e. those who are strategiaclly data driven) gain a competitive edge because decisions made are based on evidence. Whilst perhaps not a surprising general conclusion, the survey’s stats show how much of a difference being data-driven can make. For example, the survey found that “65 percent of highly data-driven SMBs financially outperform their competitors”, i.e. almost twice as much as less data-driven SMBs (33 percent).

The report also highlighted other key benefits enjoyed by SMBs that adopt a data-driven strategic approach. These include:

– Helping SMBs remain profitable and cost-efficient in the face of uncertainty, market turbulence, and evolving customer expectations.

– Being twice as likely to experience positive impacts from data across key business outcomes than less data-driven competitors, e.g. customer satisfaction (69 percent compared to 37 percent), revenue (65 percent compared to 34 percent), and cost-reduction (55 percent compared to 25 percent).

– Forecasting far more positive impact across the same key business outcomes than their less data-driven competitors, e.g. 65 percent of highly data-driven SMBs anticipate data positively impacting marketing in the next two years, compared to just 33 percent of less data-driven SMBs.

Mature Data Strategy Important 

The report also revealed that 60 per cent of organisations with a mature and comprehensive data strategy financially outperform their competitors and that SMBs with a high-level of data maturity can harness their data more effectively, thereby empowering both data managers and data consumers.

It also showed that a mature data strategy in a business fosters a data-driven culture and cross-team collaboration, enhances data governance and compliance, and reduces risk. SMBs with extensive historical data also appear to gain more accurate forecasting and customer segmentation.

Being Data-Driven Leads To Faster Adoption Of AI 

One other interesting key point revealed by the report is that “highly data-driven SMBs adopt AI at twice the rate of less data-driven competitors”. The report also appears to show that SMBs with a high level of data maturity that have invested in AI adoption can yield approximately 30 percent more value from the technology.

How Can Your Business Do The Same? 

If you’re an SMB, you may be wondering how you can leverage data to deliver some of the many positive benefits outlined in the AWS report. With this in mind, here are a dozen ideas that you could use to deliver similar positive benefits and outcomes and become more data-driven:

1. Invest in data management tools. Implement robust data management and analytics platforms to streamline data collection, storage, and analysis. For example, tools like Microsoft Azure Synapse Analytics, AWS Redshift, or Google BigQuery may help to manage your data efficiently.

2. Develop a comprehensive data strategy. Create a clear data strategy that aligns with business goals. This should include data governance policies, data quality management, and a plan for leveraging data insights to drive decision-making.

3. Utilise cloud-based solutions. Think about how you can leverage cloud infrastructure to store and process data. This is because cloud solutions offer scalability, flexibility, and cost-efficiency, making it much easier to manage large datasets and perform complex analyses.

4. Implement data lakes. Establish ‘data lakes’, i.e. centralised repositories where raw data is stored in its original format until it is needed for processing and analysis. This can be done by selecting a cloud service provider like AWS, Azure, or Google Cloud that offers data lake solutions. This approach can allow for more flexible data processing and analysis, enabling you as an SMB to extract valuable insights from diverse data sources.

5. Adopt AI and machine learning. You may already be using AI to a limited extent, but using AI and machine learning to analyse data and generate actionable insights can, as highlighted in the AWS study, help with customer segmentation, predictive analytics, and automating routine tasks, enhancing efficiency and decision-making. This kind of process could be set up, for example, by selecting a platform such as Google Cloud AI, or Microsoft Azure AI and gathering and preparing data from various sources like sales, customer interactions, and operational processes. With this data, you can build machine learning models (e.g., using TensorFlow and scikit-learn) to address specific needs such as customer segmentation, predictive analytics, and automating routine tasks. Once the models are developed, they can be integrated into business processes to automate tasks and generate actionable insights. Continuously monitor the performance of these models and refine them as needed to ensure they deliver optimal results.

6. Enhance data literacy. Consider investing in training and development to improve data literacy among employees. Ensuring that staff understand how to interpret and use data effectively can foster a data-driven culture.

7. Promote cross-team collaboration. Encourage collaboration across departments to share data insights and drive innovation. For example, tools like collaborative dashboards and data-sharing platforms can facilitate this process.

8. Leverage your historical data. It makes sense to use the historical data you already have to improve forecasting and customer segmentation. Analysing past trends can, for example, can help you to make more informed decisions and tailor offerings to meet customer needs.

9. Automate data collection and analysis. Automating the process of data collection and analysis using tools like ETL (Extract, Transform, Load) systems can reduce manual effort and improve the timeliness and accuracy of data insights. Automation of this kind can be particularly important for SMBs which typically have limited resources.

10. Strengthen data governance. Implementing strong data governance frameworks to ensure data accuracy, security, and compliance can help reduce the risks associated with data breaches and regulatory violations. Data breaches, for example, can be particularly devastating for SMBs, affecting their financial stability, customer trust, and long-term viability, so it makes sense to look seriously at this data governance issue as part of being more data-driven.

11. Utilise generative AI for content creation. Use generative AI tools to create marketing content, such as articles, social media posts, and advertisements. Analysing data on customer preferences, trends, and engagement metrics can mean that generative AI can be used to create content that resonates with customers and enhances marketing effectiveness. Generative AI can, therefore, be a way to save time and ensure a steady flow of high-quality content that is highly relevant (and could be more effective). That said, if you’re still cautious about how you adopt AI, particularly where your data is concerned, you’re not alone. For example, as the AWS study showed, most SMBs are cautious about adopting AI and are still exploring how to leverage it effectively.

Nearly half of the respondents surveyed identified security as the greatest challenge, while other major concerns include a lack of skilled personnel (43 per cent) and a general skills shortage (42 per cent). To meet this challenge, you may want to invest in upskilling your workforce, ensuring you have robust security measures, and perhaps seeking external expertise to effectively leverage AI.

12. Monitor key performance indicators (KPIs). Regularly track and analyse KPIs related to data-driven initiatives. This can help you to measure the impact of your data strategy and make necessary adjustments to achieve better outcomes.

What Does This Mean For Your Business? 

The insights from the AWS study underscore the critical importance of becoming data-driven to gain a competitive edge. For your business, this means that prioritising data and developing a mature data strategy can significantly enhance your operational efficiency, customer satisfaction, and overall financial performance. By leveraging data effectively, you can make more informed decisions, anticipate market trends, and respond swiftly to customer needs, thereby positioning your business ahead of less data-savvy competitors.

Implementing a robust data management framework and investing in the right tools and technologies, (such as data lakes and AI) can streamline your data processes and unlock valuable insights. Enhancing data literacy across your organisation and fostering a culture of collaboration can further empower your teams to utilise data more effectively. While concerns around security and skills shortages are valid, addressing these challenges through upskilling, robust security measures, and external expertise can mitigate risks and facilitate smoother AI adoption.

Ultimately, building a data-driven organisation is not just about adopting new technologies but about embedding data-centric practices into your business operations. By doing so, your business can harness the full potential of data, drive innovation, and achieve sustained growth in an increasingly competitive market. Now is the time to start laying the groundwork for a data-driven future that ensures your business remains resilient, agile, and ahead of the curve.