Unlocking Revenue Growth with Data-Driven Decision-making

Leading corporations know the value of data-driven decisioning: It drives revenue. Organizations with consistent access to pertinent real-time data experienced 50% higher revenue growth and net margins than those without.1

Advancements in artificial intelligence (AI) and Internet of Things (IoT) technology enhance a decision-maker's access to big data — massive depositories of structured, unstructured and semi-structured information from numerous sources. Data-driven decisioning-making applies multiple relevant metrics and insights for rationalized analysis and reporting. With this cogent approach, the C-suite can substantiate business concepts and theories to guide growth strategies.

Data-driven insights optimize efficiency and decision-making across the enterprise.

In-depth analysis offers a more granular view of data for streamlining operations and informed decision-making across all departments, including finance and accounting, sales and marketing, operations, supply chain management, product development and customer service. Integrating industry, market and competitive data helps corporations make data-driven decisions for the present and future.

How do data-driven decisions boost revenue?

• Improve receivables and cash flow management.

  Data-driven cash flow strategies are based on real-time information about accounts receivable and customers. Advanced processing tools — often combined with integrated Resource Planning (ERP) systems and straight-through processing — enable analysts to organize data into accurate, up-to-date cash flow reports. Decision-makers can then interpret the results, identifying patterns and behaviors that indicate problematic accounts and predict future payment risks. These data-driven insights can guide new strategies that address important aspects of receivables management, such as collections and credit policies.

• Pinpoint market needs and tailor appropriate strategies.

  Customer relationship management (CRM) software, industry reports, consumer surveys, sales channel reports, social media pages and your website are valuable data streams. Collecting and analyzing such data unveils ways to retain and grow your customer base. Business insights convey product and sales performance, user experience metrics, marketing return on investment, and other details with which to evaluate success and refine strategy. You’ll also be able to forecast demand and prepare go-to-market strategies for new products and services.

• Boost operational efficiency with precise performance metrics.

  Establishing key performance indicators (KPIs) for each department and program can improve efficiency. AI is a powerful tool to analyze and accurately report performance data, including that of core processes. Staff using AI have seen 80% productivity improvements.2

• Successfully mitigate risks for a competitive advantage.

  Data-driven insights can help identify and mitigate industry, market and enterprise risks, including predicting future vulnerabilities. For example, organizations can examine various risk factors such as wage inflation, supply chain disruptions, cybersecurity threats, government administration turnover and interest rate fluctuations. Effectively managing internal and external threats enhances resilience, safeguards assets and ensures operational stability, enabling the agility, trust and sustained growth needed in a dynamic market.

• Make decisions with greater confidence, speed and accuracy.

  Big data insights are profound, and technological advancements enable near-instantaneous processing of expansive quantities in all formats. AI and machine learning uncover, process, analyze and report data trends in mere seconds or minutes.3 Access to this vital information, in a more streamlined manner, enables corporations to make faster, data-driven decisions.

When corporations want to enhance performance in any area of the enterprise, business insights are indispensable.

Strategy is essential to data-driven decisioning.

A well-defined strategy ensures that data-driven decision-making is aligned with business goals, leverages the right data sources and effectively applies analytics to drive meaningful insights. Without a strategy, organizations risk data silos, inaccurate conclusions and missed opportunities for innovation and growth.

1. Align data strategy with corporate goals and objectives.

   The first requirement in developing a data strategy is to ensure it aligns with what the organization wants to achieve. The data types, collection infrastructure, governance, analysis and reporting methods should be tailored to the areas they’ll serve. Sales professionals typically include revenue, acquisition costs, conversion, win rates and customer lifetime value in reporting, for example. Carefully evaluate what data is needed to make decisions relevant to each area of the business.

2. Choose the right software.

   Frequently used software-based data solutions are either business intelligence (BI), business analytics (BA) or a combination of both tools. BI tools gather and report past data, making it easier to visualize trends and patterns. Tableau® and Microsoft Power BI® are two common BI tools. Conversely, BA tools offer predictive capabilities, revealing why trends happen for better forecasting. The SAS® software suite is an example of BA tools.
   
   Depending on its purpose, a software solution may analyze several types of data.
   • Descriptive statistics
     Defines or summarizes frequency, percentages, medians or averages. Often used for “snapshots” from a specific period.
   
   
   • Predictive
     Historical information, such as identifiable trends or patterns used to forecast future outcomes.
   
   
   • Diagnostic
     Collected and analyzed to determine the cause of an event or issue. Evaluates correlations or relationships between variables to deliver results.
   
   
   • Prescriptive
     Analyzes current and past inputs to recommend steps to achieve specific goals.
   
   There are many software solutions available. Be sure your selection offers the essential functions and features needed, is compatible with other technologies and scales as your organization grows.

3. Assemble a highly skilled data team.

   Overseeing big data is promising, yet challenging. The industry is growing rapidly. Experts predict tech hiring over the next 10 years will increase twice as fast as overall employment.4 Data roles vary based on company size and needs. However, a core team should include scientists, engineers, analysts and security professionals. Data engineer and scientist roles will lead tech hiring rates, with 304% growth expected.5
   
   When hiring, consider such technical skills as BA environment management, data visualization, programming, statistical analysis, governance administration and quality assurance. Soft skills should include critical thinking, attention to detail, collaboration and communication.

4. Ensure data quality and integrity.

   Business data should be thorough, accurate and timely. As should its analysis when making data-driven decisions. Reliable sources, trustworthy collection methods and stringent governance ensure data quality and integrity. Actively monitor data streams, as well as regularly reviewing governance policies and documentation.

5. Practice rigorous data security and privacy measures.

   Fraud can skew data and lead to misinformation. Breaches also compromise compliance with state data security laws and industry-specific privacy standards, as well as your reputation with customers. Implement a strong security posture that protects your network, devices and data.

6. Create a culture of data literacy.

To effectively implement a strategic plan that supports data-driven decisions, all employees should be aware of the importance of data. Depending on their roles, some will require training to read, interpret and report data related to respective areas of responsibility.

How can Synovus help with your data-driven decision-making?

Making decisions that increase your organization’s profitability requires skill and expertise. Synovus has many years of experience helping corporate clients of all sizes, in multiple industries, accomplish financial goals. For more information, complete a short form and a Synovus Treasury & Payment Solutions Consultant will contact you with more details. You can also stop by one of our local branches.