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The digital switch: eight trends in analytics catalysed by Covid-19

analytics
(Image credit: Image source: Shutterstock/ESB Professional)

The pandemic has served as a digital catalyst. Sudden and drastic changes to the world of work catapulted the corporate environment toward new requirements. Some we have long been approaching but didn’t think we would need so soon. Similarly, our individual experiences with technology have transformed rapidly - not just underpinning the way we work, socialize and communicate, but with data informing our personal liberties and behavior.

As a result, the digital development that was once linear suddenly became immediate and a ‘digital switch’ is taking place. Companies are now accelerating their digital transformation and ensuring the data they are using to make decisions is not only up-to-date and accurate, but readily accessible and understandable to drive more informed decision-making and support new business moments. As individuals, we have equally faced new challenges in how we understand and make decisions with data, as well as presenting us with new concerns around privacy and data sharing. 

On the path to achieving digital transformation, business and personal attitudes toward data are changing. Here are eight trends that have developed as a result of the ‘digital switch’ catalyzed by Covid-19:

1. Changing generational attitudes change toward analytics.

The digital switch may force a similar change to what we saw in 2008 when people moved from reporting-centric tools to analysis-centric tools to meet new, agile requirements. Now, we have a whole new set of requirements and businesses need to be much more reactive to the crisis, but also pre-act so they are prepared for future black swan events. As a result, a whole generation of business leaders is shifting their perception on analytics to be more dependent on business-ready data than ever before. 

2. Up-to-date, business-ready data is more important than ever.

The last six months have taught us that when forecasting, variables can change rapidly and disrupt planning; yet many organizations are working with data that is too old to support such an agile approach to business. This affects their ability to identify opportunities or risks on the horizon – both of which are critical to their survival in these uncertain times. Now is the time to ensure that analytics engines are not only set-up to show the most pertinent insights to enable fast, informed decision-making, but that the data integration processes from all systems – whether ERP, CRM or SaaS applications – can feed them in real-time.

3. Capturing and synthesizing alternative data has become essential.

While investment firms have long used alternative data - like audio, sentiment, and aerial photos - to capture information at an early stage and use it to inform decisions, it’s potential is being rapidly recognized in new industries. In today’s unpredictable business landscape, other sectors have begun to see the value in mining alternative data to help them read signals earlier and establish a clearer picture before making a decision.

4. SaaS is everyone’s best friend.

Even the most conservative companies with the biggest inertia are moving toward ‘as a service’ to help them offer more services to their employees and customers remotely. Many have done this to enable operations to keep running in times when we can’t go into the office. Other have also adopted software-as-a-service (SaaS) to take advantage of high computing power in the cloud, such as artificial intelligence (AI), to drive greater efficiencies. While the focus is on SaaS right now, to co-exist with on-premise, this shift will be the start of bigger data integration and migration efforts. This holds a lot of promise, but businesses should be aware that when applications are configured into SaaS, the cloud software processes can result in data being locked-in.

5. Business process reengineering is taking center stage.

Business Process Modelling has been around since the 90s. But because of technological advancements, we now have an opportunity to mine what the processes looks like to automate and optimize them. For example, using Process Mining and Robotic Process Automation (RPA). When combined with embedded analytics, processes can be established that allow insights to trigger automated actions. For resource-constrained organizations, this unlocks massive potential for their data to drive true active intelligence that both augments their employees and relieves them of simple, rote decisions.

6. Moving from self-service to self-sufficiency.

As a result of widespread working from home, companies have disproportionately been favouring attractive user interfaces to help their employees ‘self-serve’ their data insights. We’ve also seen that many users don’t want to manually self-serve at all. Instead, they expect algorithms to do work for them, surfacing micro-insights and stories before they build a dashboard. We’re also seeing that users want to be self-sufficient in accessing and querying the data directly – facilitated by natural language, improved business logic and data catalogues, ensuring that our increasingly distributed workforces are self-sufficient earlier.

7. A nationwide need for data literacy.

We’ve seen an explosion of data, visualizations and storytelling in the public discourse. Data has become increasingly important in not only informing workplace decisions, but also our behavior as individuals in response to the pandemic. However, with data at the center of government communications around case numbers and contact tracing, people are beginning to recognize the limitations of their data literacy. With the growing risk of Covid misinformation disproportionately affecting those with poor numerical literacy, it has never been more important to drive public education around data literacy to help them identify false information. But, of course, this cannot be fixed overnight. We, therefore, must also build a data etiquette whereby rules are established for the proper and comprehensible use of data in the public discourse.

8. The compass for surveillance and security has been recalibrated.

Many people recognize that data is at the heart of the fight against the pandemic. While actions taken by governments across the world differ, the one thing that binds them all is that both local and global data has informed their response. In turn, this has led to a shift where an increasing number of people see it as their civic duty to share more data than ever before with authorities and medical researchers to help them understand the virus and how it spreads. But while we have allowed these greater intrusions on our privacy today, it will be interesting to monitor this change in the long-term and for how long breaking down data privacy barriers for things like contact tracing will be accepted.

A digital-first world

The digital switch increased our dependence on technology and data in a way that the world has never seen before. Timely access to accurate information is informing every aspect of our lives and is fundamental to not only the ability of companies to survive in this environment, but in helping us manage the virus and identify the safest ways that we can interact with society. Now that this shift has begun, the transformation that we will see in the way that data is used to accelerate innovation and improve the services that we interact with every day will be phenomenal. These are the eight trends I recognize today that will lead us down that path, but I watch with anticipation to see what 2021 holds.

Dan Sommer, Senior Director, Qlik

Dan Sommer, Senior Director at Qlik.