How to measure and maximise your analytics investment

It is safe to say that data analytics investment is key for any business to thrive on the modern market. But not without measuring the right KPIs and other key factors. Discover great tips here.

Investing in data analytics is the key to improving business prospects. With the right analytics platform, organisations can transform the way they work, making smarter decisions, improving insights and eliminating inefficient processes. However, to make the most out of their data analytics platform, organisations need to know how to maximise their investment and set the right measurements in place. In this blog, I explain the best way organisations can measure and maximise their analytics investment.

Measuring the value of your analytics investment

There is no value in an analytics investment if the correct measurements are not in place. While the specific measurements (or KPIs) vary depending on industry and business objectives, they should cover the following areas: Quality, speed and robustness.


High-quality data should be relevant to an organisation. To measure an organisation’s data, you need to have the right KPIs in place, which varies based on industry. For example, if you are in retail, your KPIs would be sales and inventory and, for finance, a key KPI would be expected ROI. Finally, hotels would consider revenue and room occupancy levels as relevant KPIs. With the right KPIs in place, you can optimise the analytics platform to focus on the right variables, making it easier to gauge and measure the correct business outcomes.


Often an overlooked factor in measuring an analytics investment, robustness is the ability to yield good results despite unexpected changes. For example, a change in the market is going to affect an organisation’s bottom line or an unexpected outbreak forces an NGO to reallocate its resources. Organisations need robust data because circumstances change and data should be able to account for these changes. Data should be detailed and comprehensive enough to anticipate several scenarios and project predictions based on simulated situations.

To accomplish this, you need to use machine learning and Decision Optimisation. Machine learning forecasts different situations. These situations are added to the Decision Optimisation model, which in turn, predicts the effect of alternative decisions.


Your data analytics model should collect and analyse data in quick time. The faster the analytics model works, the bigger your competitive advantage. An analytics platform that comes with sophisticated technology, like Decision Optimisation, allows data analysts to work faster. However, there is no definite timeframe for speed as this varies depending on the skill of the data analyst and how familiar they are with the data analytics platform. This is where a well-established company like SAS comes into play as most SAS products are designed for efficiency and speed, optimised by a team of SAS experts who know the platform inside and out.

Maximising the value of analytics investment

Measuring the right KPIs is not just about variables, it is about knowing how to maximise value.

Make sure data is interconnected

For most companies, their data is within a silo. However, having information in a silo only undermines the gains made from data and reduces the effectiveness of your platform. To get the most out of your data, you need to break the silos and interconnect the different variables. Accomplishing this is incredibly challenging, but in the long run, you can maximise your analytics investment.

Selecting the right analytics platform

Many organisations select the wrong analytics platform for their need and goals. The mistake occurs because decision-makers focus on a platform’s capabilities rather than the organisation’s needs. To maximise your analytics investment, it is important to choose a platform based on its ability to address your business’ problems, instead of just raw capability. Hence, the reason why SAS builds different analytics products to address specific problems like banking fraud.

Focus on useful, not interesting KPIs

Choosing the right KPIs is crucial for attaining success in your analytics investment. Sadly, many organisations make an error in this area by focusing on what is interesting and not what is useful. For example, when reporting digital marketing returns, the CEO does not care about the specific keywords that got traffic. However, they are going to care about the type of media that attracted the most visitors and how that is from last quarter’s strategy. Focusing on the right KPIs not only focuses on the right business problems but makes reporting much easier.

What does it all boil down to?

To maximise your analytics investment, organisations need to set the right KPIs and maximise the value of the current analytics platform. Maximising utility means giving due diligence to the right platform, the most relevant KPIs and making sure data is connected. To make sure the analytics platform is providing genuine value to your organisation, you have to select the right KPIs. The specific KPIs will change depending on the organisation, industry and objectives. However, in our experience, we find that the most suitable areas to focus on are quality, robustness and speed.

If you are eager to learn more about data analytics, then visit our blog for more information.


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