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As more businesses adopt the digital economy, leaders are faced with a decision. Are you continuing down the traditional path, or will you use digital analytical capabilities to find more actionable insights?  Department Leaders and IT Managers who choose to capitalise on this opportunity will find themselves challenged to harness data meaningfully while grappling with the limitations of their digital infrastructures.  

We look at the essence of digital analytics, with the aim of offering pragmatic strategies business leaders can use to transform data into a strategic asset that drives data-driven decisions and competitive advantage. 

Overcoming Inadequate Infrastructure 

Disjointed legacy systems and pieced-together software solutions form a huge hurdle in a company's digital analytics capability. Disorganised data will not support coherent decision-making and results in missed opportunities and lower growth.  

Two action points stand out above any others to start effectively:

  • Consolidate Digital Tools: Integrating analytics tools into a single platform creates a unified data environment. This makes the process of gathering, analysing, and acting on data seamless. Look for platforms that offer modularity, allowing them to grow and scale as your company does. 
  • Leverage Cloud Computing: Cloud-based analytics platforms lower the barrier of entry with greater affordability and adaptability. They move your data & analytics infrastructure beyond the physical confines of an employee’s laptop, providing more powerful analytical tools and storage solutions with minimal upfront investment. 

Bridging Expertise Gaps 

When we investigated what companies report as their key challenges to becoming more data-driven, they reported seeing substantial skills gaps in their current teams. Adopting a data-first mindset is all about getting started smartly and taking a pragmatic approach to this issue: 

  • Create Training Opportunities: Develop just-in-time training programs for employees that cover data literacy, analytic methods and the application of insights to business strategy. When this training is well-timed, this knowledge empowers teams to identify and interpret relevant data points effectively. 
  • Expand Data Teams: Hire or develop data analysts and data scientists who delve deeper into analytics. These specialists are more capable of discovering patterns and guiding strategic decision-making. This in turn ensures that investments in analytics translate into tangible, quantified business outcomes. 
  • Partner with Experts: Sometimes, the fastest route to expertise is to collaborate with external consultants or agencies that specialize in digital analytics. This is particularly true when you are developing a digital analytics function from scratch or want to augment the team with very specific knowledge you don’t need full-time. This quickly fills gaps and provides a solid foundation for in-house capabilities. 

Leveraging Analytics for Competitive Edge 

For the segment of companies sized 50–1000 employees, digital analytics represents an opportunity to level the playing field with larger competitors or even accelerate beyond them. While there are numerous areas where analytics drives competitive advantage, here are three of the most powerful ones:

  • Refine Customer Targeting: Digital analytics helps identify ideal customer profiles, enabling you to tailor marketing campaigns that resonate with the right target audiences, minimising the required marketing spend while maximising ROI. 
  • Increase Operational Efficiency: Apply analytics to operations and supply chain management to boost profitability or reduce cost. Data-driven insights help find areas for process improvements, waste reduction, and cost savings, directly impacting the bottom line. 
  • Innovate Product Development: Utilize analytics to capture customer feedback, analyse usage patterns and predict market trends. This information accelerates innovation and aligns product development with consumer needs, creating products and services that outperform competing offerings. 

Embracing Digital Analytics in Core Business Functions 

When implemented correctly, each functional business area stands to benefit from digital analytics. By integrating analytics into core business functions, organizations not only uncover insights that drive efficiency, innovation and revenue, but also extend their data-driven strategic approach to each team. 

  • Sales 
    • Pricing Optimization: Leverage digital analytics to optimize pricing models by looking at patterns, competition and customer data. Pricing optimisation increases competitiveness while maintaining profit margins. 
    • Enhancing Cross-sell and Up-sell: Analytics predicts which customers are more likely to be interested in additional products or upgrades, allowing sales to proactively target them with the right product ant the right time. Your sales team will increase average order value and customer lifetime value. 
    • Churn Reduction: By analysing customer behaviour patterns and satisfaction levels, sales teams get the insights they need to proactively address issues and reduce churn rates. 
  • Finance 
    • Predictive Financial Modelling: Develop models that predict future financial scenarios based on historical data, helping to guide strategy and investment. 
    • Expense Management: Use analytics to highlight areas where expenses can be reduced without impacting business performance. 
    • Revenue Attribution: Understand which products, services, or business activities are contributing most to revenue, focusing efforts on the most profitable areas. 
  • Marketing 
    • Customer Journey Analytics: Map out the customer journey with analytics to identify key touchpoints and optimize interactions at each stage. 
    • Content Performance Analysis: Find out which types of content drive the best engagement and conversion, informing and refining your content marketing strategy. 
    • Market Basket Analysis: Understand which products or services are frequently bought together to inform bundling or cross-selling strategies. 
  • Supply Chain 
    • Inventory Level Optimization: Analyse sales data to maintain optimal inventory levels, reducing carrying costs and the risk of stockouts or overstock. 
    • Supplier Performance Scorecards: Create scorecards to objectively evaluate and improve supplier performance and compliance. 
    • Logistics Network Analysis: Utilize data to design an efficient logistics network that reduces delivery time and costs. 
  • Human Resources 
    • Workforce Analytics: Use analytics to gain insights into workforce structure, productivity, and workforce planning. 
    • Diversity and Inclusion Measurement: Track progress on diversity and inclusion initiatives using relevant data points. 
    • HR Process Automation: Identify HR processes that can be automated to free up time for more strategic human resource management. 

Enabling all business functions to leverage digital analytics allows companies to act with the insight and agility of larger and more established competitors. This data centric, data driven approach enables everyone in your business to make more informed decisions that accelerate performance. 

What’s Next? 

While the barriers to starting with analytics may seem extensive at first, the rewards are extensive. Data is a strategic asset that informs every business function about the best way forward. It not only optimises what you do today, it unlocks opportunities to innovate and accelerate beyond the competition. 

By acting smartly, business leaders lower the barriers to entry. Leverage low-cost cloud solutions that scale as you grow and unify your data in a single view. Use expertise where it’s needed and build your own team’s knowledge. If you’re wondering what that path may look like, we recommend reviewing our solution path ‘Mastering the Data Analytics Lifecycle: A CIO and Data Scientist's Guide’. 

Vasilij Nevlev
Post by Vasilij Nevlev
January 31, 2024
Vasilij is the founder of Analytium and the driving force behind its innovative approach to Data & Analytics. His career is characterised by a data driven mindset, which he now uses to achieve great results for others.