5 key ways you can gain benefits from data analytics today
Data is now the world's most valuable resource. Named the 'oil of the digital era' by the Economist, the abundance of data is fundamentally changing the nature of business as we know it. With advances in robotics, artificial intelligence, and machine learning ushering in a new age of automation, leaders in every sector will soon have to grapple with the reality of big data.
Everyone talks about using data to gain insights that drive better decisions. But what does data really mean for your business, and what steps can you take to start capturing value from it now? We believe there are five key ways you can realise the benefit of this new and ubiquitous commodity today.
1. Data visualisation
Raw data comes at us with overwhelming velocity and volume. But we are fundamentally visual creatures, so graphical representations will always prove more insightful to us than columns and rows of numbers.
That's why data visualisation is so important; it allows anyone from within an organization to quickly grasp difficult concepts and identify new patterns within data without the need for complex analysis. David McCandless, a data-journalist, and information designer, illustrates this point perfectly in his 'Information is Beautiful' talk.
However, the ability to visualise data is too often seen as a 'nice to have' tool within businesses rather than a necessity – leaving valuable insights unearthed and the potential for change never fully realised. All business functions make decisions, so data needs to become commonplace.
The latest generation of visualisation tools are easy to adopt and offer an immediate business advantage and effective storytelling. They can also be a useful way of establishing best practice ways of looking at your data.
2. Data diversity
More data often means more insight. But it isn't always simple to obtain; data diversity requires tackling disparate sources, varied data sets and unstructured data. Unsurprisingly, many businesses have fallen at this hurdle.
In fact, it shouldn't matter where your data is stored – it could be in Hadoop, a data warehouse, in the cloud or on your desktop in Excel. The data could even be structured, semi-structured or unstructured. For example, Unilever have successfully combined weather, sales and social data to optimise their advertising spend within marketing.
Ultimately, as long as you are employing the current wave of data blending tools like Alteryx, you can bridge the gap between all these sources. With a significantly improved delivery approach, you can create a repeatable process that takes minutes to refresh, not weeks. If you need practical tips on how to build baseline data for your analysis, download this free sample chapter.
3. Agile analytics
Time is key to gaining actionable insights from data. Traditional business intelligence projects take years to come to fruition, and long-term breakdown in visibility often results in a solution that doesn't fit the original requirements.
Agile analytics is turning traditional BI on its head and dramatically reducing the time to value. With the advent of new tools, actionable business insights can be delivered in just months or even weeks.
Key to success here is collaboration. By combining raw data, a set of hypotheses and people with domain knowledge, analytics experts can quickly test iterative processes to create a working solution. Such quick delivery enables you to decide whether a long-term implementation is right for your business. You can read more about reducing time to value with agile analytics in one of my earlier blog posts.
4. Self-service analytics
There is a misconception that working with data requires advanced programming skills. This might have been the case in the past, but with the rapid developments in technology the barriers have been lowered.
Now, we all have the capacity to become data scientists. Every team within your business can get value out of data using widely available analytics tools, and basic training can go a long way – as shown by our own graduate analyst's experience learning Tableau.
At Concentra, we are increasingly working with businesses to upskill their employees as part of the agile approach to analytics, ensuring that development is kept close to the front line of the business. Our experience of training hundreds of client teams across all functions and roles demonstrates how big the uptake can be.
Remember that self-service doesn't have to mean self-sufficiency. You can blend data and build visualisations yourself, but you'll ultimately need the support of a strong IT infrastructure; the soda fountain analogy is an excellent way to think about the difference between the two.
5. Advanced analytics
Advanced analytics is not new. But it is becoming increasingly prevalent, even for those without a PhD. Right now, we are working with FMCGs to automate assessments on forecasting processes, and with banks to create their own recommendation engines.
Many businesses use analytics to understand and learn from what has happened in the past. As data becomes more important to your organization, you may move from 'descriptive' analytics to 'prescriptive', i.e. where should your business go next?
However, before embarking on this journey you need to ensure that you have the right processes and tools in place. Start by becoming confident with your historical data first, before looking towards the future.
Want to find out more about how you can gain more value from data? Get in touch with one of our team today to discuss your business requirements.