Safe Software: Making the Impossible Possible Using Spatial Data
In a bid to keep up with the demands of the pandemic, many organisations have invested billions into new tech to help drive digital transformation and run more data-driven businesses. According to research from KPMG, a whopping $15B more was spent per week on tech as the pandemic took root and companies sought new ways to navigate these unprecedented challenges.
Whilst this approach has been a necessary part of the journey, on its own, it hasn’t been enough. Many businesses have failed to address the other critical side of this digital transformation equation: their people. Specifically, they have underutilised and overburdened the professionals who can not only use these new tools, but leverage them to provide value for the whole organisation.
With the current landscape continuing to urge agility and resilience to meet the demands of evolving markets and consumer behaviours, unlocking the importance of data at scale, for every employee, is vital for business success. Rethinking the role of the data analyst therefore becomes crucial for companies who want to gain a competitive advantage and get the most out of their analytics, in order to make impactful decisions for the future of their business.
Becoming more proactive and autonomous in driving strategic business change through the use of data analytics is key to this. TDWI’s latest report in collaboration with ThoughtSpot, "What Modern Analysts Want”, found that the usage of advanced analytics like machine learning is expected to grow by more than 50% over the next few years. This signifies that as data solutions are advancing, their use cases are becoming more sought-after. If companies do not upskill their current workforce to be able to use these technologies they will be left behind. As such, businesses need to allow their analysts to deliver more than just reports by empowering the non-specialist departments to source their own tailored data-driven insights. This creates a new internal structure which will act as a vehicle for universal data access and in turn, an adaptable business.
But as we move forward with this new data model, what can the role of the modern analyst evolve into, to both suit the growing demands of the business and empower analysts to proactively solve deeper complexities with data?
What’s keeping analysts from stepping into the future?
With 66% of research respondents finding that one fifth of their reports don’t provide actual value to the business, it is clear that many analysts are not being used to their full potential. What’s more, businesses must overcome a variety of barriers to make analytics accessible. For example, complex data infrastructure and data illiteracy were listed as the top challenges for organisations by 49% and 39% of respondents respectively.
When upskilling the workforce, businesses should lean on their analysts to facilitate this process. If leaders are investing heavily in realising the true value of their data, they must also hone in on what their data teams are spending time doing, and how the entire workforce treats data. Allowing analysts to turn their focus towards more intricate work, such as data pipelines and cloud integrations, means that they have the opportunity to pass on their knowledge to the rest of the business. This works in tandem by also giving individuals another skill set to add to their own portfolios.
Organisations can achieve this mutual upskilling by providing employees with the right technologies to leverage easy access to insights. By empowering the workforce to answer its own data questions, through both search and predictive analytics, businesses can help their employees make smarter and more data-driven decisions. This solves queries faster, helps to streamline operations, and leads to a cycle of improved business results as there is no barrier between the insights and those with detailed business context.
The TDWI research suggests that the main reason why businesses and analysts haven’t already embraced this model is because of the lack of company-wide data democratisation. 44% of analysts believe that this is a necessary requirement within their workplace which they are not currently seeing implemented. This calls for a cultural shift: companies need to create data transparency and encourage their workforces to drive all business decisions with data in front of mind. This must be rewarded and driven from all directions, including the C-suite, so that everyone can feel confident and empowered to use data to its full capacity.
Leading a shift towards democratisation
While pitfalls are plentiful, they are not inevitable. Those who are willing to embrace change and move beyond legacy systems such as working in data silos will be able to utilise their analysts’ talent and start boosting the data skill set of the entire workforce. It is these businesses which will see the rewards of upholding operations that are driven by accurate and real-time insights, allowing staff to make confident decisions for the betterment of the organisation.
Overall, democratising data is essential for organisations looking to scale up their analytics efforts to adapt to an ever-changing environment. Search and AI-powered analytics solutions can help companies on this journey, by providing users with the flexibility to glean instant tailored insights from their data. As organisations roll out their plan for the evolution of the modern analyst role, such tools will become a crucial component to their tech stack. By creating a culture where processes and decisions are supported by tangible insights, businesses can reap the benefits of an empowered workforce where data is king.