Why all businesses must have a data analytics strategy

Uncertainty and anxiety about the future are new realities for many SMEs. Decision-making and problem-solving are two major factors keeping business owners and executives awake at night. The good news is that, regardless of the size of the organisation, virtually every problem or business decision can be addressed using data analytics.

Capturing and making sense of organisational data is now giving business leaders an edge. It offers operational resilience and predictive accuracy and helps drive precise action that improves business performance and profitability.

All organisations, regardless of size, must have a data analytics strategy to remain competitive. It’s common for SMEs to view data analytics as something big organisations do, but they should realise that it is applicable to everyone in business.

It’s also important to understand how to make data analytics work for each business. For example, SMEs often face challenges when it comes to the types of data they collect and how they use it. Data collection can be as straightforward as compiling customer information in a simple spreadsheet or as complex as collecting data from thousands of pieces of equipment every second, culminating in hundreds of millions of data points collected each day. To avoid confusion and unnecessary effort, businesses need to identify what kind of data will help them solve their key challenges and focus on collecting and analysing that data.

According to the global Analytics Impact Index, only eight per cent of businesses lead with data analytics, and Chinese businesses come out on top. Conversely, Australian organisations lag behind when it comes to the maturity and impact of their data and analytics capabilities. Deloitte’s Global Perspectives for Private Companies Report, released in 2018, showed that more than 40 per cent of Australian private companies planned to invest in business intelligence and data analytics; however, they were daunted by the fact that data analytics spanned such a broad range of capabilities including data integration, data management, data warehouse, machine learning, data modelling, and application design. However, companies that did become data analytics leaders achieved 60 per cent more profits.

It may seem overwhelming to develop and implement a data analytics strategy. Getting the foundations right is critical in achieving a data-driven, insights-led culture, no matter the size of the business or industry in which it operates. SMEs should start with a clear view of the strategic objectives and the key issues they are looking to solve.

Data analytics plays a vital role in equipping decision-makers with the ability to anticipate problems and market changes before they occur. For example, by analysing a customer’s pathway through an organisation, organisations can optimise the journey to make it as smooth as possible for customers, eliminating pain points that may lead to dissatisfaction. For example, data can be used to identify the points where conversations are repeated, knowing at which point of the process the most complaints come in, and identifying which parts of the process take too long. This helps organisations improve internal processes and efficiencies, reduce costs, and enhance the customer experience. It can also be used to identify where technology can remove costly, manual, repetitive tasks.

Businesses will be left behind if they don’t start leveraging data analytics, particularly in the increasingly fast-paced digital economy.

Some businesses don’t realise just how much quality data they have to help grow their business, while others are overwhelmed by the amount of data they have and don’t know where to start. Some would say that failing to leverage data can be viewed as tantamount to negligence; it is as fundamental as that.

Srdjan Dragutinovic, Director – Data Analytics, RSM Australia

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