When even some digitally-transformed organizations could not maximize value from their data, the time is ripe to adopt analytics-ready data management
The buzzword of the year has to be digitalization or digital transformation. In the year prior, this term was already trendy in many countries in the region: it means “the adoption of digital technology to transform services or businesses, through replacing non-digital or manual processes with digital processes or replacing older digital technology with newer digital technology.”
Now, with battered economies and industries simultaneously struggling to recover amid trade wars and international tensions, digitalization has been made a mandate everywhere. Why? Because just before Jan 2020, much of the world was still modernizing at its own pace, unaware of the fulminant force of global lockdowns and social distancing measures.
Suddenly, businesses were not just the only casualties. Entire governments, social enterprises, educational systems and even e-commerce sectors were suddenly faced with existential concerns about continuity and relevance. Even organizations that were already at some level of digitalization were hard pressed to keep operations secure due to insufficient business continuity planning and heightened cybercriminal activity.
Somehow, the world managed to pull through the critical first waves of coronavirus chaos. As we pick up the pieces behind us and learn from those critical months of hard lessons about operational resilience and agility, every sector of society is rushing into the me-too mentality of going digital. Awash with government stimuli to ‘digitize or dematerialize’, everyone is told to ‘do everything online’, ‘tap the growth trends in e-commerce’, ‘go cashless and be customer-oriented’, and so on.
A good start but get the basics right
For sure, it has never been a better time to transform digitally. Every government is eager to speed up economic adaptation to the new world order and will offer grants, rebates and subsidies to any organization inclined to survive.
However, even among corporations that were leaders in self-disruption and digitalization, one inevitable result of being fully digitalized is the need to manage the huge amount of digital data collected. Cloud computing has made it easy to store the data until data scientists could figure out what to do with it. Edge computing has made data sensing and collection even faster and easier—to the point that many organizations—from enterprises to governments—have had to keep the data in disparate siloes until they have had a chance to monetize or share the powerful insights trapped inside. The longer such valuable data is stored and exploited, the less the returns on investment.
In the current global economic crisis, the need to collect usable digital data (digitalization) is one hurdle that many organizations have to start overcoming. The less well-known implication is that organizations must digitalize with the mindset to use data to its fullest potential.
According to Geoff Soon, Snowflake’s Managing Director for South Asia: “Organizations need to come up with robust business continuity strategies to thrive in the ever-changing market. Part of this strategy is instantaneous access to critical business intelligence data. Cloud technology provides a platform that enables access to data, anytime, anywhere, and from any device. It provides an infrastructure that can support the business during times of crisis such as the COVID-19.”
The point to be made is: digital transformation laggards will be off to good start if they finally embrace digitalization at a scale and speed that quickly modernizes operations, but any organization (digitalized or otherwise) that cannot extract and exploit the value of collected data will still be disadvantaged.
Data-driven intelligence and collaboration
As the age-old saying goes: disposable money sitting in the bank earns you less than if you invested it well. The same applies to data: collecting and storing Zettabytes of data in separate data warehouses will actually reap us less value than if we actually found a way to clean it, centralize it and invested the insights on how to improve organizational planning.
There is another saying about money that can be applied to data: “Data is like fertilizer. Left in a few piles it is useless and it stinks, but spread it around and share it, and great things will happen.”
Case in point: Vital COVID-19 data from each country would have been less useful unless it was openly shared. Although the gigantic data sets were already in the Cloud, organizing, consolidating and sharing the information would have been difficult. However, with the help of a cloud data platform, the immense amount of data stored in different formats was ultimately made shareable and actionable.
Similarly, businesses rushing to digitalize can plan ahead to avoid running into the same problems that some transformation leaders faced after storing siloed data: the more information is accumulated and untapped, the higher the cost of storing it, and the higher the depreciation of the actionable data locked within the bits and bytes.
According to Geoff, “cloud data platforms offer scalability and flexibility with unlimited storage capability. During tough times when the use of resources needs to be optimized, businesses benefit from cloud data platforms by paying only for the compute and storage they actually use.”
Geoff reiterated that, as COVID-19 continues to disrupt industries, businesses will need to make quick decisions to resume operations in a strategic manner. “Organizations can accelerate the pace by leveraging the capabilities offered by cloud data platforms rather than digitalize without foresights about data mining, analytics and monetization,” said Geoff.
The data-silo situation in APAC
A recent IDC study of APAC businesses revealed that organizations creating data-to-insights (D2I) capabilities were more resilient and poised for survival and growth in the current period of uncertainty and fierce survival pressure.
Virtually every company (96% or higher) surveyed across APAC reported a significant challenge in identifying which data sources were valuable. Singapore recorded the highest rate of this challenge (100%), followed by India (98%), Australia (97%), and Japan (89%).
The average D2I score was 41.8 across the APAC region. India showed the highest overall score at 47.4, with Australia close behind at 42.4. Singapore and Japan carried the lowest scores at 38.8 and 38.5, respectively.
Regardless of regional differences, the survey has shown that digitalization does guarantee the ability to maximize the value of data if unintegrated and leaky data pipelines, exist often due to a lack of a data cataloging and change data capture capabilities.
In addition, investments in AI and analytics are being undercut without an agile, automated, and agnostic data pipeline that continually transforms data from any cloud, system or source into enterprise-ready information that drives action and outcomes.
Foreseeably, when digital transformation is implemented with centralized, agile data-management in mind, enterprises around the world will be able to share (anonymized) data in a form of ‘competitive collaboration’ that is a win-win proposition for a COVID-enlightened humanity.