Spot emerging data trends with optimised BI
Efficient data analysis capabilities are now as indispensable for successful businesses as the computers themselves they run on. The insights gleaned from business intelligence (BI) tools play a crucial role in helping companies develop a holistic overview of their business operations. This enables them not just to look at the present – identifying bottlenecks, delivering actionable reports and streamlining processes – but also the future – spotting emerging trends and boosting efficiencies that help the company maintain a competitive advantage.
It’s no surprise then that 98 percent of companies use BI tools, according to a recent Dimensional Research study. What is surprising is the same study’s finding that despite the tools at their disposal, companies still waste the time and energy of their top data talent.
The abundance of data is a good problem to have – if you can deal with it
Digital transformation has resulted in a data boom across businesses but having access to the most recent, relevant and reliable data remains a challenge. Look no further than the current pandemic to understand why – with customer behaviour and business models in constant flux, data from even just a few months ago is often no longer relevant today.
The way human resources are used in making sense of data is crucial to success. Data analysts continue to play a central role to the innovative powers of forward-thinking companies, but increasing the quantity of analysts goes a little way if the quality of the work they do cannot be improved. More than ever, businesses need their data analysts to focus on deriving insights from the data sources rather than being bogged down with the steps that precede the actual analysis.
This, unfortunately, is the stark reality according to the Dimensional Research study. The approximately 500 data professionals surveyed across five continents admitted they only spend 50 percent of their time on analysing data. Data analysts are instrumental in unlocking the insights that influence strategic business decisions, but when only half their time is spent on the actual analytics, suddenly it becomes clear that companies are far from unlocking the full potential of this key resource.
The report findings
In the survey, access to data was identified as one of the top challenges data analysts face in their day-to-day operations. It further revealed that:
- Data analysts waste a third of every single workday trying to access the data they need, with data sources cited as being unreliable, broken or intermittently accessible
- Nine in ten data analysts said their work had been hindered by frequent unreliable data sources over the past year, slowing them down and clogging up the process
- Six in ten said they are required to update the schemas – the blueprints for the way in which data sources are constructed – every month to ensure business decisions are based on the most up-to-date data
- 60 percent said they are held up in their work several times each month waiting for engineering resources to support these updates
The findings clearly indicate that data analysts are stretched thin, wasting time on tasks extraneous to their job description such as creating reports in Excel because they cannot access data via dedicated dashboards. When organisations scale or adjust their focus to unlock new avenues for growth, data is in constant movement with fresh data sets being introduced and existing data re-cut to answer new questions.
To match data analysis capabilities to new business needs and aid the decision-making process, analysts must be able to create reports with a high level of accuracy, which requires the most up-to-date data. But one unavailable or inaccessible data source is enough to wreak havoc and cause widespread delays in delivering actionable BI across the organisation. It is alarming then that 86 percent of companies admit to working with out-of-date data and 41 percent of data analysts had used data that was two months old or older, by which point data is practically useless – and even misleading. Organisations today need to be able to think quickly and modify business operations to keep up with changing economic circumstances, as the pandemic clearly demonstrates. Using two-month-old data to underpin business intelligence and decision-making can result in organisations adopting unsustainable or straight out damaging practices.
Automating data pipelines reveals profit-driving insights
Still, there is reason for optimism. 68 percent of analysts said they have ideas for driving more company profit, which they could implement if given the time. The solution, however, is not hiring more data analysts to deal with badly managed data – the answer is better data integration.
Companies should rethink data transit with a focus on enabling analysts to spend more time analysing and less time finding, fixing and stabilising data. By automating the data integration process, organisations can remove these hurdles from the way, enabling data analysts to spend all of their time on vital analytics. This way data analysts can easily add new data sources and rapidly extract data from multiple sources, including multiple cloud-based applications. Moreover, when data pipelines require no maintenance, analysts no longer need to waste time waiting for engineering resources to make data available.
Empowering data analysts and making the most of Business Intelligence investments can only start by making data as easy to access as possible. With analyst resources properly supported, revenue-driving and data-backed decisions will follow.
SAS: Improving the British Army’s decision making with data
SAS’ long-standing relationship with the British Army is built on mutual respect and grounded by a reciprocal understanding of each others’ capabilities, strengths, and weaknesses. Roderick Crawford, VP and Country GM for SAS UKI, states that the company’s thorough grasp of the defence sector makes it an ideal partner for the Army as it undergoes its own digital transformation.
“Major General Jon Cole told us that he wanted to enable better, faster decision-making in order to improve operational efficiency,” he explains. Therefore, SAS’ task was to help the British Army realise the “significant potential” of data through the use of artificial intelligence (AI) to automate tasks and conduct complex analysis.
In 2020, the Army invested in the SAS ‘Viya platform’ as an overture to embarking on its new digital roadmap. The goal was to deliver a new way of working that enabled agility, flexibility, faster deployment, and reduced risk and cost: “SAS put a commercial framework in place to free the Army of limits in terms of their access to our tech capabilities.”
Doing so was important not just in terms of facilitating faster innovation but also, in Crawford’s words, to “connect the unconnected.” This means structuring data in a simultaneously secure and accessible manner for all skill levels, from analysts to data engineers and military commanders. The result is that analytics and decision-making that drives innovation and increases collaboration.
Crawford also highlights the importance of the SAS platform’s open nature, “General Cole was very clear that the Army wanted a way to work with other data and analytics tools such as Python. We allow them to do that, but with improved governance and faster delivery capabilities.”
SAS realises that collaboration is at the heart of a strong partnership and has been closely developing a long-term roadmap with the Army. “Although we're separate organisations, we come together to work effectively as one,” says Crawford. “Companies usually find it very easy to partner with SAS because we're a very open, honest, and people-based business by nature.”
With digital technology itself changing with great regularity, it’s safe to imagine that SAS’ own relationship with the Army will become even closer and more diverse. As SAS assists it in enhancing its operational readiness and providing its commanders with a secure view of key data points, Crawford is certain that the company will have a continually valuable role to play.
“As warfare moves into what we might call ‘the grey-zone’, the need to understand, decide, and act on complex information streams and diverse sources has never been more important. AI, computer vision and natural language processing are technologies that we hope to exploit over the next three to five years in conjunction with the Army.”
Fundamentally, data analytics is a tool for gaining valuable insights and expediting the delivery of outcomes. The goal of the two parties’ partnership, concludes Crawford, will be to reach the point where both access to data and decision-making can be performed qualitatively and in real-time.
“SAS is absolutely delighted to have this relationship with the British Army, and across the MOD. It’s a great privilege to be part of the armed forces covenant.”