"Data-driven mastery: Why SMEs should harness big data for major gains"

"SMEs and a full-blown data strategy? Really, now - who would’ve thought they’d need something so fancy?"

In today's data-driven world, data collection has long been a challenge for small and medium enterprises (SMEs). While large companies and startups have integrated data strategies into their operations, many SMEs still struggle with this integration. The lack of sufficient knowledge to develop the business internally, the difficulty in finding the right skills and the associated costs discourage many of them. But data can level the playing field, giving them the ability to compete with larger businesses. But before you can do that, you need to develop a data strategy and make smarter choices on how to allocate resources.

I recently read a report from the World Economic Forum’s Centre regarding data in SMEs. The report surveyed hundreds of them and identified several challenges and opportunities. Key findings include:

• Obstacles to extracting value from data: According to the World Economic Forum’s Centre report, 75% of SMEs struggle to maximize the value of their company’s data investments.
• Not integrated IT systems: The report indicates that 55% of SMEs experience difficulty in finding and maintaining data within their company’s systems.
• Missed opportunities in global markets: Only 36% of surveyed SMEs operate in more than one regulatory jurisdiction, as highlighted in the report.
• Insufficient monitoring and reporting of sustainability data: The report also reveals that only 25% of SMEs are somewhat familiar with “carbon disclosure” sustainability reporting systems but are unsure of the business benefits.

However, the report highlights that while challenges exist, particularly in data reliability and decision-making, the strategic adoption of big data technologies is not only feasible but also imperative for growth and competitiveness.

Why data strategy matters for SMEs

Data has become a vital asset for businesses of all sizes. For your SME, a well-crafted data strategy can unlock numerous benefits, including improved customer insights, cost management, and better operational efficiency. It can even facilitate a complete business turnaround. By making data-driven decisions, you can compete more effectively with larger enterprises, respond swiftly to market changes, and tailor your products and services to meet customer demands.

However, without a clear data strategy, you risk being overwhelmed by the sheer volume of data available or, conversely, missing out on valuable insights. A data strategy helps you prioritize your data-related activities, ensuring that resources are allocated to the most critical areas and that data is used in a way that supports your overall business strategy.

Key steps to developing a data strategy

Align it with your business objectives: The foundation of any data strategy is a clear understanding of your business’s goals. Whether your focus is on improving customer satisfaction, increasing operational efficiency, or expanding market share, your data strategy should align with these objectives. Start by identifying the key business questions you need to answer and the data required to address them.

Assess your current data capabilities: Evaluate your current data landscape to understand what data you have, how it is being used, and where there are gaps. This assessment includes reviewing existing data sources, the tools used for data collection and analysis, and the skills available within your organization. Understanding the current state of data management will help identify areas needing improvement or investment.? Even within seemingly straightforward ERP or CRM systems, it is possible to integrate a broad spectrum of information. For example, in a previous project, I implemented at first classification system for all items based on just three primary criteria: family, sub-family, and supplier. This straightforward segmentation significantly enhanced the organization’s analytical capabilities, particularly in sales and purchasing, by enabling more detailed analysis of factors such as seasonality, supplier distribution, and sector performance.

Prioritize data initiatives: Given the limited resources for many SMEs, it is essential to prioritize data initiatives that will have the most significant impact on your business. This could involve focusing on improving data quality, enhancing customer insights, or optimizing supply chain operations. By prioritizing initiatives, you can ensure that your data strategy delivers tangible results without overextending resources.

Implement data governance: Data governance is critical to maintaining data quality, security, and compliance. You should establish clear policies and procedures for data management, including data collection, storage, access, and usage. This ensures that data is reliable, accurate, and protected, reducing the risk of data breaches and ensuring compliance with regulations such as GDPR. For the many SMEs that respond to public & private markets, don't overlook this point! It is now a prerequisite for obtaining these contracts.

Invest in the right tools and technologies: The right tools and technologies are essential for implementing a successful data strategy. You should consider investing in scalable data management and analytics platforms that fit your needs and budget. Cloud-based solutions can be particularly beneficial for SMEs, offering flexibility, scalability, and cost-effectiveness. There are many solutions available (CRM and ERP), and many of them offer free versions for you to try out. So don’t hesitate to explore these options!

Develop data skills: Building data capabilities within the organization is crucial for the success of the data strategy. You must invest in training and development to enhance the data literacy of your employees. This includes not only technical skills for data analysis but also the ability to interpret data and use it to inform business decisions.

Monitor and adapt the strategy A data strategy is not a one-time effort but an ongoing process. Continuously monitor the effectiveness of your data initiatives and be prepared to adapt your strategy as your business evolves or as new data challenges and opportunities arise. Regular reviews of your data strategy ensure that it remains aligned with your business goals and continues to deliver value.

La Redoute: A comeback fueled by data strategy

La Redoute, a French fashion and home décor founded in 1837, has been a well know SME name in France for decades. Known for its mail-order catalog, the company struggled with the transition to the digital era in the early 2000s. As online shopping grew, La Redoute faced declining sales and financial difficulties, leading to a major restructuring in 2014.

By investing in data analytics, the company segmented its customer base, enabling personalized marketing efforts that included tailored product recommendations and targeted advertisements. Additionally, La Redoute optimized its inventory management through data insights, reducing excess stock and ensuring that popular items were always available.

The company also enhanced its online user experience by analyzing customer behavior and continuously improving its website and mobile app, which led to higher conversion rates. Furthermore, La Redoute used predictive analytics to stay ahead of fashion trends, ensuring their product offerings were in line with customer preferences.

This data-driven approach resulted in La Redoute's return to profitability by 2017, with significant growth in online sales, increased customer loyalty, and re-established market leadership.

Overcoming common challenges

While developing a data strategy, SMEs may encounter several challenges, including limited resources, data quality issues, and the complexity of data management. Here are some practical tips to overcome these challenges:

Start small: Focus on a few high-impact areas where data can drive immediate value. As the organization gains experience and confidence, the scope of the data strategy can be expanded.

Leverage external expertise: Partnering with external consultants or service providers can offer specialized knowledge and tools for data management and analysis, They can help too to assess your current data strategy maturity . This can be particularly beneficial if you lack in-house expertise.?

Promote a data-driven culture: Encouraging a culture where data is valued and used in decision-making is essential. Leadership should champion data initiatives and demonstrate the benefits of data-driven approaches.

Don’t use Excel as your main data analysis solutions: Excel has long been a staple in data analysis, known for its accessibility and versatility. However, as data needs grow more complex, its limitations become apparent. Excel really struggles with large datasets, lacks real-time data capabilities, and can create collaboration issues when multiple users are involved. I've personally experienced it several times. Excel is very handy at first, but as the volume of data increases, Excel became slow, prone to crashing, and difficult to manage.

These challenges make it less and less suitable for today’s fast-paced, data-driven business environment. The shift doesn’t have to be immediate; you can start by integrating BI tools into specific areas where they can make the most impact, gradually and smoothly transitioning away from Excel

In conclusion, if you run a small or medium-sized enterprise, embracing a data strategy might seem daunting, but it's an investment more in leadership and vision than in heavy finances. The principles laid out might sound like common sense, but the difference between businesses that adopt these strategies and those that don't is stark. Being data-driven allows you to dynamically adapt and seize opportunities that others might miss. It's about making smarter decisions that are grounded in reality rather than guesswork. The challenge isn't in the cost—it's in the commitment to steer your enterprise using data as your compass. Make that commitment, and you'll see just how transformative data can be. Let the success stories of others inspire you, but remember: the path to innovation and growth is yours to forge.