Here’s why data, automation and security make up the holy trinity for success.
Besides building resiliency in their business model, navigating successfully through the turbulence will require maturing and mastering technology capabilities in three key areas, shares Shanker V Selvadurai, VP & CTO at IBM. Discover why data-driven insights, automation at scale, and securing all touchpoints are crucial to success.
More than two years ago, something unexpected occurred. The COVID-19 pandemic accelerated digital transformation essential to the survival of businesses and organizations during the crisis. This year, in the wake of rapid shifts in the macroeconomic and geopolitical environment, leaders of enterprises are facing a confluence of structural uncertainty – supply chain disruption, labor and skills shortage, rising energy prices, and inflationary pressure – each reinforcing the other. Organizations, big and small, have entered a potentially long and perfect storm. It will be critical to continue the digital transformation that held them in good stead during the pandemic.
With growing market volatility and competitive pressures, access to the right data at the right time is crucial to recognizing trends early to mitigate risks, as well as to seize new opportunities. However, data that is complete, current, and accurate data is imperfectly accessible in most organizations. Utilizing incorrect data can lead to legal actions, compromised security or biased decisions with severe consequences.
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According to Capgemini, The Data-Powered Enterprise, 2021, 73% of business executives are unhappy with their data quality, and 61% of organizations are unable to harness data to create sustained competitive advantage. Real-time decisions and actions require data hosted in multiple locations, stored in different formats and sometimes only available through intermediaries under restrictive conditions. Data sprawl in a hybrid and multi-cloud environment is a reality for most organizations. Additionally, rising nationalism across the world is also driving stricter regulatory requirements on data sovereignty and residency.
Addressing these challenges will require rethinking where and how data is captured, processed, and stored. A data management architecture that supports consistent data capabilities across the organization’s network – on-premises and multiple cloud environments – is needed. The right data should be available “on the tap” at the right time and place. There should be no expensive movement of data to perform analytics; different business units should own and manage their own data without having to consolidate platforms, and decisions can be made more in real-time and closer to the point of interaction or engagement. Instead of point-to-point connections or costly and complex single-hub style data collection, a data fabric will “span” a virtual or logical net across disparate and hybrid data sources. The virtual net is established through an intelligent knowledge catalog that leverages active metadata, knowledge graphs, semantics, and machine learning. Managed centrally but distributed across the landscape, the catalog orchestrates when and how data is delivered, as well as what is visible to whom to ensure privacy and trust.
Key complexities enterprises need to navigate
Digital acceleration during the pandemic also saw organizations piling on more technical debt as they needed to act quickly. Fractured digitization on a disaggregated IT landscape has increased the complexity with not just siloed data but also disconnected processes across the application estate. According to IDC, 83% of organizations estimate they will have up to 1,000 applications in their portfolio in five years. It is increasingly challenging for humans to manage this complexity on their own effectively. In addition, the workforce has also been significantly impacted by the Great Resignation, as well as the millions of workers dealing with the long-term effects of the virus. Employers and employees are dealing with challenges related to immigration disruptions, shifts in workers’ expectations and mental health issues. This labor volatility is having a direct impact on organizational productivity and economic growth.
Organizations that build capabilities using intelligent automation are poised to address the risks associated with labor uncertainties and talent supply. The infusion of AI enables the scaling of automation in industries forced to rely on a reduced workforce or intentionally trying to minimize human interaction. Intelligent automation systems understand signals from data in a way that is similar to humans but can consume data with far greater speed. They can also learn from interactions and respond accordingly to automate workflows that link processes end-to-end, straddling siloes and cutting across functions to expose new outcomes that differentiate an organization from its peers. IBM Institute for Business Value expects 80% of intelligent automation early adopters to outperform their competitors significantly. Automated workflows impact revenue by enabling businesses to meet customer needs seamlessly and consistently, particularly during periods of uncertainty.
When the pandemic began, millions of employees started to work from home and are continuing to do so. Every work-from-home employee or hybrid worker connecting remotely represents an expansion of an organization’s attack surface and creates new openings for threat actors. The increased digitization of products and services by organizations during this period has further added potential entry points for cybercriminals. A growing number of siloed constituents are accessing resources – employees, suppliers, partners, and customers – all using multiple devices from distributed and remote locations. Perimeter-centric security models cannot cope with the dynamic nature of this incredibly large attack surface. In addition, these attacks move fast and infect machines in seconds. The problem is exasperated with multiple security tools in the organization that generate alerts on the same attack, making it difficult to understand the incident.
Organizations need to modernize their threat detection and response capability. Silos need to be eliminated to gain visibility across data sources – from the cloud to core systems. Workflows must be unified without the need to pivot between tools. A zero-trust framework is required to help organizations manage the risks of a disconnected business environment while still allowing users access to the appropriate resources. This approach uses context to securely connect the right users to the right data at the right time under the right conditions while also protecting the organization from cyber threats. AI and analytics continuously validate connections between users, data, and resources. The IBM, Cost of a Data Breach Report, 2022, found that organizations that adopted zero trust saved nearly USD 1 million in average breach costs compared to organizations without zero trust deployed.
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The COVID-19 pandemic taught us that the digital economy could present substantial growth opportunities for organizations as well as provide resiliency against threats to the traditional customer journey. Strengthening core data, automation and security capabilities will be critical for companies to serve customers better and find new sources of value during periods of change and uncertainty.
These competencies are also the foundation for accelerating innovation by leveraging other exponential technologies like 5G, edge computing, Web3 and quantum computing. And they are equally important to support new business imperatives like sustainability challenges. These are extraordinary times, and it is important that we consciously and purposefully rethink architectural and technology decisions, not just to weather the storm but to come out better and stronger.
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Vice President & CTO, IBM Asia Pacific
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