Data analytics for business decision-making isn’t just for large corporations. In fact, because small and medium-sized businesses (SMBs) have more flexibility to act on insights, they may stand to gain even more from business data analytics—think actionable insights, improved efficiency and profitability, and a more level playing field to boost competitiveness.

You don’t need a large finance team or an advanced complex analytics infrastructure to start seeing benefits. Here’s how to set up a meaningful practice using the resources you already have.

The Power of Data Analytics for SMBs

For modern businesses of any size, data analytics is more than a tool—it’s a strategic capability that builds competitive edge by enabling informed, proactive decision-making for growth both now and in the future. Tracking metrics over time and developing a regular cadence of insights helps SMBs do things like:

  • Reduce costs and inefficiencies 
  • Identify trends to optimize resources and investments
  • Spot points of failure and improve quality and customer service
  • Improve marketing through hyper-relevance and much more

Data analytics also brings confidence and speed to activities like product planning and pricing, market expansion, hiring and scaling operations.

The flip side of the coin is risk mitigation. Business data analytics plays an especially important role in SMBs, where things like delayed deliverables, unforeseen sales surges, and flawed forecasting can be detrimental.

Even the most basic analytics setup can support your long-term goals by empowering you to make incremental, data-driven choices along the way.

Minimum Viable Metrics: What You Need To Start

Data analytics is a means to end. To start, you need a goal. Think about the business outcomes you want to achieve and keep it simple. For example: Cut costs. Free up cash to invest somewhere new. Root out inefficiency. Improve customer experience. 

Pick one or two. You don’t need a broad, all-encompassing strategy for transformation here. For now, your data engine is on training wheels. Get the hang of it, then go bigger.

Next, identify five to eight key performance indicators (KPIs) to support your goals. What data points do you need to measure your outcomes and help you make better decisions around them? For example, if you want to improve customer service, you can start by asking, “What’s our issue resolution rate? How long does it take to service a customer inquiry?” These questions can point you toward the specific metrics you need. 

You’ll probably start by tracking core financial metrics, such as:

  • Cash conversion cycle to see how well your business manages working capital and liquidity
  • Gross margin to see how efficiently you produce goods and inform cost control and pricing
  • Earnings Before Interest, Taxes, Depreciation and Amortization (EBITDA) to track profitability and overall performance
  • Sales revenue to identify trends and areas of improvement

Tracking these metrics and others regularly is the foundation of data analytics in business. 

Setting Up Basic Data Analytics for Your Business

Now it’s time to mobilize the above information by creating a dashboard that houses all your data in one place and helps you visualize and monitor it.

  • Choose a dashboard platform. There are plenty of user-friendly tools out there to help you do this, from everyday spreadsheets to low-cost business intelligence tools with prebuilt dashboards you can choose from. Your CRM platform might even have the analytics you need built into it. (Here’s a great tutorial on how to build a dashboard in Excel.)
  • Gather the data sources you need to measure your KPIs. Ensure your sources are accurate, reliable, and compliant with your regulatory demands and ethics. Common sources of data include:
    • Sales data from point-of-sale systems and e-commerce platforms
    • Customer data from CRM and email marketing platforms
    • Website data from Google Analytics
    • Social media analytics tools
    • Accounting software such as QuickBooks and Xero
  • Input your data manually or import it automatically. You can automate this by creating connections to data sources via “queries,” which are instructions for the program you’re using to retrieve and manipulate data from a given source, like a database, another workbook, Office Data Connection (ODC) file or your transaction list from your point-of-purchase provider. It sounds complicated, but many platforms have “recommended” queries or application programming interfaces (API) integrations baked in that make this part easy and low-touch.
  • Use your platform’s automated features to display, summarize and analyze your data in ways that are helpful to you and your stakeholders. These features, such as PivotTables in Excel, help you slice and dice data in different ways to identify patterns, create reports and make decisions more easily.
  • Keep your data clean and updated so your insights remain fresh and relevant. Automate as much as possible: Use real-time data connections, schedule automatic data refreshes if possible and check regularly to ensure your data connections are intact. Periodically review your dashboard to update or remove outdated or irrelevant metrics and visualizations.

Translating Business Data Into Financial Insights

There are countless ways to leverage data for forecasting and strategic decision-making, but here are a couple of straightforward approaches to start with:

  • Time series models analyze historical data over time to show patterns such as spikes or dips, which SMBs can use to anticipate a seasonal surge and ramp up accordingly. Think about visualizing time series data in bar charts to see comparisons or scatter plots to see correlations.
  • Regression models allow you to see how certain factors like a promotion or a news cycle might influence business outcomes. For instance, you could predict how a weather event might affect operations and adapt strategy in advance. Think about the types of patterns to look for: upward/downward, seasonality, cyclicality, irregularity, correlations/relationships, and thresholds or breakpoints.
  • Budget variance analysis illuminates the difference between your budgeted and actual expenses and revenue to show whether you’re on track to meet your objectives.

Compare your findings to benchmarks, then turn signals and patterns into actionable insights by asking questions like: Why is this happening? What are the implications in the short- or long-term? Frame your thinking around your KPIs. What opportunities does it create? What actions can you take?

Example #1: Your data shows declining revenue over three consecutive quarters. 

  • Why is this happening? Weakening demand? Market share loss?
  • What actions can we take? Scale back marketing spend if ROI is poor, freeze hiring, delay nonessential projects, etc. 

Example #2: Your data shows a sustained increase in revenue.

  • Why is this happening? Is a younger generation aging into your service? Have customers found an alternate use for your product you didn’t think of?
  • What actions can we take? Ramp up marketing, invest in R&D for new products, increase operational capacity, etc.

Becoming a Data Analytics-Focused Company

Even without a dedicated analytics team, SMBs can stand up a meaningful business data analytics practice. Start with simple metrics, readily available data and free or low-cost tools. Focus on relevant KPIs and use data to answer specific business questions. Look for incremental improvement, and gradually build your capability as your business scales.

And if you find you need more guidance or bespoke support, get help from Paro’s financial planning and analysis (FP&A) experts for greater impact and peace of mind. These qualified consultants help provide deeper visibility into your business to make data-based decisions and prioritize the right actions for growth.

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