Find out what's going wrong, and how you can respond:
One of the most common reasons you might be failing to derive actionable insights from analytics is a lack of clear objectives from the outset. Without a defined purpose aligned to business goals, data analysis becomes a directionless endeavour.
Businesses often collect data because they can - not because they know what they want to achieve with it. This leads to a scenario where vast amounts of data are gathered, but none of it aligns with specific business goals, amounting to wasted resources alongside potentially harbouring compliance issues.
As we laid out in the first article of this series 'From Data to Decisions' , you need to start with a clear understanding of what you want to achieve.
How to fix it:
You may be suffering from the effect of data silos, where data is stored in separate systems or departments and is not easily accessible across the organisation. This can be caused by historical ways of working, or equally by over-implementation of different data and analytics tools, leading to many disconnected data pots.
Fragmentation makes it difficult to get a comprehensive view of your business. Without unified data, patterns and relationships can be overlooked, or may never even be discovered. This will leave you with incomplete data, and a potentially misleading analysis.
How to fix it:
Low quality data is a major obstacle to gaining actionable insights. Inaccurate, incomplete or outdated data can lead to incorrect conclusions, potentially causing you to make poor decisions.
Data quality issues often arise from incorrect data collection, inconsistent data entry, lack of validation processes or use of outdated technology.
How to fix it:
Are you falling into the trap of over relying on analytics tools and technology, expecting them to automatically deliver insights? We all need to be particularly mindful of this, as technology increasingly leverages AI to take the heavy lifting out of data analysis, or decrease the time to insights.
While advanced analytics platforms are powerful, they are only as effective as the human expertise behind them. Google Analytics and Data Studio are merely tools. Without the right analytical skills behind them, you might struggle to interpret their data correctly or fail to ask them the right questions.
How to fix it:
Analytics often fail to produce actionable insights when data is analysed in isolation, without considering the broader context. For instance, a spike in website traffic may seem like a positive trend, but without understanding the source of the traffic, the quality of the behaviour of that traffic, or the market conditions at the time, it’s difficult to determine if this data point is meaningful.
Analytics need to be contextualised within their environment, not only to validate the outcomes, but also to make them actionable.
How to fix it:
Whilst it's important not to analyse data in isolation, be aware of analytics becoming overly complex too. Ensure that you surface data into analytics tools as easily as possible, and present that data in a way that connects easily to your audiences.
When analysis is too complex, it can be challenging to extract clear, straightforward recommendations. Any resulting insights will only lead to more questions, rather than paving the way to actionable decisions.
How to fix it:
Do you focus on descriptive analytics – what happened in the past – and forget to leverage predictive analytics, which can provide foresight into future trends and behaviours? Whilst descriptive analytics can be valuable, they won't necessarily guide future actions.
Predictive analytics, as described in the second article of this series, ‘Choosing the right analytics’, uses historical data to forecast outcomes and guide proactive decision making.
How to fix it:
So you're successfully extracting insights from you data, but are you acting on them? Hindered by resistance to change? Lacking alignment between departments? Or missing the chance to communicate insights to decision-makers? Whatever the barrier, when insights aren't acted upon, the value of analytics is lost.
How to fix it:
Whether you're looking for help overcoming any of these obstacles or simply need practical advice on getting the insight you need from the data you already have - we can help.