The best ways for small and medium-sized enterprises to increase productivity with data management

Many small businesses start out managing their clientele, orders or invoices manually in order books or simple spreadsheets. This works well for a while until they grow, increase their team and customer base, and their payables increase. As they grow, it doesn't take long for them to lose track of everything.

At that point, most companies decide to invest in digital solutions, whether it's accounting software or a tool to automatically create invoices. Many also invest in sales and marketing solutions soon after - if they haven't already.

This first step toward digitization offers tremendous opportunities. In addition to their immediate purpose, such as creating invoices, these tools collect data on all events and processes and often map them visually in charts or in clear statistics.

This provides companies with useful insights into their operations and the preferences and habits of their customers that would otherwise remain hidden. We will explain below how you can use data management to increase your productivity.

Why data management is important

Data management refers to the collection, entry, storage, processing, and deletion and archiving of all of a company's data records. Data analytics, on the other hand, refers to the evaluation of these vast amounts of data. It extracts hidden patterns, market trends and customer preferences.

Together, the two technologies offer the following advantages, among others:
  • easy access to data
  • No cumbersome search for information
  • all employees have access to the same up-to-date data
  • prepared, clean data enables well-founded decisions
  • Data analysis is the cornerstone of personalization
Only when data management and data analysis are working, companies are able to track and measure key performance indicators (KPI). These insights can then be used to optimize processes - laying the foundation for productivity gains.

How to use data management to increase productivity

The reasons for low productivity or productivity gaps are often outdated technologies or bottlenecks in processes. Some of these are obvious, such as the time-consuming manual creation or payment of invoices, while others only become apparent after these processes have been digitized.

Thanks to data management and data analysis, weak points in the company can be uncovered and remedied, while at the same time you can recognize important opportunities. Did you know, for example, that a modern customer relationship management system (CRM system) can give you clues about which leads are most promising or when you should contact a lead again before it goes "cold"?

Only those who collect appropriate data can make targeted and efficient decisions and take action. Your sales reps can then focus on these promising customers and provide them with an individualized offer directly tailored to their needs.

With this type of data monetization, in addition to increased productivity, your company will directly reap measurable economic benefits through more successful sales and increased revenue.

5 tips for increasing productivity with data

The benefits of data are obvious. But how can small and midsize businesses use data management to increase productivity?

1. use the right technology

Choosing the right tools is critical to success. Above all, the tools you choose must fit your business and your needs. Think about the following questions:
  • How much technical expertise do you and your team bring to the table?
  • Do you prefer a cloud or on-premise solution?
  • How user-friendly and intuitive should the tool be?
  • What is your financial framework?
  • Can the tool grow with your business?
  • Does this tool support other applications and can different business units and departments be linked into it?
  • Does the tool offer intelligent features such as AI or machine learning?
  • Can you automate tasks to provide direct relief for your team?
  • Don't rush the selection, but test a promising tool extensively before making your decision.
2. Automate data analysis using artificial intelligence.

The true value of data lies in its analysis and evaluation. Of course, you can send your data to an external processor and have them prepare and analyze it.

However, it is easier, faster and often more cost-effective to use software that is already equipped with comprehensive analysis functions. In this way, it can automatically draw the best conclusions from its data in the background with the help of artificial intelligence and machine learning and present them clearly in dashboards and graphics.

Such dashboards should also be personalizable so that you can track exactly the data and key performance indicators (KPIs) that are also relevant to your operation.

After some time, you will be able to draw initial conclusions and comparisons. Which KPIs have improved or deteriorated? What are the reasons for this? Based on this data, you will be able to identify optimization opportunities.

3. Optimize your productivity metrics using data.

How do you actually measure productivity in your company? In the manufacturing industry, the formula productivity = input / output still applies today. The input is usually the time worked and the output could be a number of items produced. Unfortunately, this formula says nothing about the quality or cost of the work performed.

Instead of measuring the time invested, rather measure the quality and focus on concrete KPIs that fit your business processes. This could be the profit or turnover per employee, the processing time for a specific task (for example, the creation of an invoice), the number of visitors on the website, the Net Promoter Score (to what extent customers would recommend a product to others), and much more.

4. Derive new insights from data

Analyzing your operational data can reveal some amazing insights - both positive and negative.

both positive and negative. Maybe that one key account isn't as profitable as you always thought. Maybe your last email campaign was much more successful than you assumed. Maybe you're surprised at the channel customers are using to get to your website.

If, for example, you find that almost no one is coming to your website via Instagram, you could either adjust your social media strategy or put your energy and resources into other platforms. It may be that your target audience prefers to use LinkedIn.

Use these insights for product development as well and adapt your existing service offering to your customers' wants and needs.

5. rethink your sales and marketing strategy

Data and numbers are essential for sales and marketing. This is especially true if you rely on advertising and market your products via Google Ads or Facebook Ads.

If you target the wrong audience, Google and Facebook alone will be happy about the revenue from your ads. Only companies that know their clientele intimately know which products or promotions they can score with. Targeted advertising campaigns can then also be extremely effective and profitable. But only then.

So keep adjusting your sales and marketing strategies and measure the results. This is the only way to identify trends and quickly adapt to new customer requirements.

Data is the new gold

Data management and data analysis are indispensable tools for companies of all sizes. Only companies that have detailed insights into their operations can be efficient and productive.

And only companies that have a 360-degree view of their customers can offer products and services that the market actually demands.

Data is the new gold of the 21st century. So make the most of your data's potential, increase your productivity, and make your company competitive in the long run, too.