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Data-Driven Transformation: Scaling Insights for Business Impact

Investment in data analytics and customer insights increased by 54% in 2024*. Three out of five organisations are using data analytics to drive business innovation**. The numbers are impressive. However, they fail to capture how many companies have yet to scale their data strategies across their operations.

No one doubts the value of data-driven insights. Companies with a data-centric culture are 58% more likely to achieve revenue goals than non data-driven companies. They are 23 times more likely to top their competitors in customer acquisition and 19 times more likely to stay profitable. Moreover, the tech and tools that allow many businesses to leverage their wonderful data are already widespread.

 

Who exactly is data-driven?

Yet, the number of companies that have scaled their data strategies and are putting data at the centre of their decision-making processes is still relatively small. It could be as low as 23%. At this figure, it makes you wonder whether predictions like Gartner’s that 65% of B2B sales organisations, for instance, will have transitioned from intuition-based to data-driven-based by 2026 will come true.

So, what’s going on? Why are businesses failing to scale their data strategies and become data-driven, as you might expect?

 

Want to become more data-driven? Download our ebook today to find out how

 

The question of scale

In our experience, many strategies are often confined to a particular area of a business. Insights are typically derived from local data rather than enterprise-wide systems and third-party sources, resulting in missed opportunities.

Companies struggle to expand their data insights beyond a few systems. Without a clear strategy, they are unsure how to progress and effectively integrate data from different parts of the company and beyond to gain a better understanding.

Moreover, because the data-driven aspect of their operation stands alone, decision-making at an organisational level becomes inconsistent and disagreements arise with personnel using a mix of intuition and data to shape their viewpoints.

 

What are the challenges in scaling data insights?

Here are seven common challenges when it comes to scaling your data insights across the business:

  • Data Silos – Data across departments is fragmented, residing in siloes, making it difficult to unify and extract comprehensive insights business-wide.
  • Data Quality – Duplicated, flawed and inaccurate data is often found across an organisation. Integrating data from multiple sources in multiple formats can be complex.
  • Infrastructure scalability – The scalability of the underlying IT infrastructure may need to be improved to support growing data storage requirements and processing needs.
  • Data integration – Integrating multiple data sources to establish a single source of truth (SSOT) for analysis is complicated.
  • Data Governance and Compliance – Data regulations are evolving, with strict rules for using, storing, and protecting data. Data security, privacy, and regulatory compliance will become more complex as data volumes increase.
  • Talent Shortages – Finding the talent to drive a data strategy can be difficult with current labour shortages. It requires expertise in managing and optimising large-scale data systems.
  • Cultural Resistance – People are often resistant to change, and altering decision-making routines is a good example. There may also be a lack of data literacy and scepticism about the value of data insights.

 

How to navigate the challenges

The best way to navigate the challenges of scaling your data insights is by developing a clear strategy. It’ll help address the issues more cost-effectively and in a timelier manner. All of the following should feature in your plan:

  • Upgrade your infrastructure – invest in solutions that process and store large amounts of data.
  • Data management – consolidate data from multiple sources for analysis in a centralised data warehouse or lake to establish consistency and a SSOT.
  • Enable automation – significantly reduce the labour involved in manual data tasks and the risk of errors, helping ensure data accuracy and reliability. Microsoft Power Automate, which automates workflows and business processes, is a good example of the technology in action.
  • Use row-level security – ensure that access to data in your data warehouse or lake is governed by row-level security so people see only the relevant data.
  • Invest in training – give employees the support they need to embrace data-driven insights. Improving data literacy will foster data democratisation across the organisation.
  • Foster a data-driven culture – develop an environment where the enterprise values and understands data. A previous blog will give you guidance on creating such a situation.

Continuous improvement should also feature in your plan. You want to review your progress and consider where enhancements can be made. You must refine your plan regularly to ensure your data strategy stays aligned with your business objectives.

 

Your step-by-step process to begin your scaling journey

Here’s a more detailed approach to start scaling your data insights:

1. Define a strategy with clear goals, objectives and a timeline – Make sure your data strategy aligns with your business goals. You want to prioritise your data projects and investments, ensuring resources go where they will deliver the most impact. Also, you can break down your strategy into manageable phases with a timeline.

2. Assess current capabilities, tools and tech stack in place – Conduct a comprehensive assessment of your data infrastructure by doing the following:

    • Evaluate existing data assets across the organisation
    • Determine the quality, consistency, and accessibility of current data
    • Assess your infrastructure for data storage, processing and integration
    • Consider the infrastructure’s ability to scale over time as your needs grow

3. Centralise data management – Collect, store and manage your organisational data in a single, unified location. Providers such as Microsoft offer centralised management solutions to support your data strategy end-to-end. For instance, Microsoft Fabric is an integrated platform offering a comprehensive data management and analytics solution.

4. Bridge the gap by investing in tech and tools – As the last point implies, scaling up your data insights will require investment. That’s not to say existing investments will have been wasted because chances are they can be integrated with a larger, centralised platform. Microsoft technology offers good interoperability and is committed to developing platforms that work well with legacy technology.

5. Start building your data pipelines for a SSOT – With the tech and tools in place, you can establish the data pipelines to create your centralised SSOT. The pipelines will extract data from multiple sources, clean it, and transform it to ensure consistency.

6. Identify the models and reporting for your data – You want to choose the appropriate modelling techniques for the insights you’re trying to achieve. These can include:

    • Descriptive analytics for summarising historical data
    • Diagnostic analytics to identify patterns and relationships
    • Predictive analytics to forecast future trends
    • Prescriptive analytics for recommending actions

It’s also important to consider how best to report insights to your audiences. How data literate are the different audiences? Reporting tools are available, giving you plenty of options.

7. Plan to ensure widespread internal adoption of your insights – As mentioned, you must develop data literacy and create a data-driven culture. Training programs are essential, and senior executives need to offer visible support. Also, celebrate any progress individuals or teams make on their digital journeys.

8. Stay focused on data privacy, governance and security – Governance and security should be at the heart of any strategy. You want to foster a culture that highly values data governance across the business. You can also leverage tools that help automate and support governance and security tasks.

9. Review adoption and gather feedback – Run surveys and assessments to monitor improvements in data literacy and gather feedback from employees and stakeholders on the effectiveness and usability of the data tools. What’s more, look for data-driven decisions in key business areas.

 

How we can support you

However, with our expertise in data strategy development, we’ll likely be able to help and provide you with a solution to get back on track and achieve your scaling goals.

At Ipsos Jarmany, we follow an outcome-driven approach that, with our experience and skillsets, helps customers fast-track their data strategies. We’re also experts in the latest tech and tools, giving leading businesses the insights to move the needle on their KPIs.

Get in touch, and let’s start a conversation about scaling your insights today.

Join forces with Ipsos Jarmany to turn your 2024 goals in to reality

* https://europeanbusinessmagazine.com/business/businesses-increase-data-analytics-investment-by-54-in-2024-new-study-reveal/#:~:text=A%20new%20report%5B1%5D%20from,experienced%20positive%20impacts%20on%20profits.%22

** https://explodingtopics.com/blog/data-analytics-stats

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