Data. To borrow a quote from Winston Churchill, “It’s a riddle, wrapped in a mystery inside an enigma”, but let’s just refer to it as the data enigma for now. What does that mean, and why should you care?
Data represents the promised land of customer insights, better decision-making, and hyper-personalised offerings for customers. When organisations capture every engagement, transaction, decision, click, search, and idea, they have all the data they need, just waiting to be analysed and mined for insights. Or so it may seem.
Having all the data you need doesn’t mean it can all be used. In fact, too much data can be as big of an issue as not enough as it doesn’t automatically transform into opportunities, reports, charts, recommendations and, ultimately, actions by itself. It takes a lot of work to organise, maintain, and restructure your data to meet your needs. For years, the promise of data analytics kept coming up against the realities of data silos, structured and unstructured data, and no coherent way to connect data from different systems.
In the early years of data analytics, this became the IT Department’s problem as they had the tools and the expertise (later aided by data engineers and data scientists) to extract, transform and load data (ETL tools) into a single repository before undergoing deduplication and standardisation so that it could be used in static reports. The challenge was that these reports quickly became outdated and couldn’t meet the evolving needs of the business. Any changes to fix them often required days, sometimes even weeks before an updated version would be available. However, there was still enough value being realised for the analytics market to continue evolving.
During this evolution, the development and availability of self-service tools like Power BI enabled citizen data analysts to arm themselves with the skills needed to create their own reports and dashboards, reducing the dependency on IT.
This sped up the time-to-value of analytics, starting an arms race where the speed of insight generation became a key driver of business success, and the next phase of data analytics began. However, with each department doing its own reporting, multiple versions of essentially the same report would exist. The insights extracted could also vary considerably depending on which sources of the data the author had access to, and how all the disconnected data was assembled.
However, the original problems of disconnected data and data siloes still existed, compounded by a number of things organisations kept doing that would hinder their data analytics journey, such as:
This is essentially the data enigma: having everything you need – the data, the tools and the promised benefits, but you still can’t or don’t take the steps to realise those benefits. The data is the answer, but also the core problem.
The value of analytics has been proven repeatedly, yet many organisations still haven’t taken the steps to do something about the data challenges that hold the promise of analytics back.
A 2022 report by NewVantage Partners backs this up when it comes to organisations becoming data-driven. Only 39.7% of organisations reported they were managing data as an enterprise business asset, and just 19.3% say that they have established a data culture. Yet this same report indicated that 97% of participating organisations are investing in data initiatives, with 91% also investing in AI.
This shows that most organisations can see the promise of getting analytics right and that AI will likely hold the key to truly transforming the analytics market and what’s possible. Enough has been written about the transformative power of the recent advances in AI technology, so we won’t dig deeper into that topic in this blog, but it is important to remember that the consequences of this change will be profound. Organisations that can’t or don’t embrace an AI-enhanced, data-driven capability will have a serious disadvantage.
Getting started on the principles of an AI data-driven culture may only require you to look closer at your Microsoft 365 subscription. With Power BI included in the Microsoft 365 E5 subscription, organisations already have what they need to turn data into insights and get more value from the investments they’ve already made. With AI insights in Power BI, organisations can also use pre-trained machine learning models that enhance data preparation efforts. With Text Analytics and Vision in Power BI they can apply different algorithms from Azure Cognitive Services (without needing an Azure Cognitive Services subscription) to enrich data in Power Query.
Using these powerful, self-service analytics tools puts you on the data journey path. To get started, though, maybe you should ask yourself, “What is the cost of doing nothing?”
Sounds simple, but we all know it’s not easy. In fact, 80% of Data#3 customers reported that “not knowing where to start” was a key barrier. Also, ensuring alignment between IT teams and business decision-makers is a key success factor before any data journey is taken, as is minimising common mistakes so that a tangible ROI can be achieved.
Data#3’s dedicated analytics practice was built to manage this scenario. Our Data Journey Map was designed to help solve all your complex data challenges and turn data into actionable insights, no matter where you are on your data journey.
There are five components of the data journey:
Every business we speak to has made some form of attempt to harness the power of data analytics. Some are successful, but most are still in the early stages of effectiveness. The challenges holding analytics back can all be traced back to data and the lack of progress towards becoming a data-driven enterprise.
With the power of cloud services, AI and the pace of innovation and competition, a new era of data analytics is here, and businesses need every advantage they can get to ensure they’re not left behind. Your data contains the answers – you just need to know how to get the insights out.
At Data#3, we have developed Analytics Accelerators that leverage our 5-step engagement process to ensure you achieve specific outcomes. These include:
One thing is certain, the insights shared in this blog highlight a clear message: the time to act is now. Our team of Analytics and AI specialists are ready to help you decipher the data enigma for your organisation. Get in touch today to discover how we can help you develop a strategic plan that enables you to fully leverage analytics and AI in your daily operations.