It is no secret that digital transformation is in full swing in Asia Pacific, with IDC already having predicted that organizations in the region would have spent US$375.8 billion towards digital transformation in 2019.
With market differentiation being critical to success, APAC businesses will continue to distinguish themselves from their competitors based on data. The one’s who are most successful will use their data to:
- Mitigate compliance, regulatory and security risks
- Find brand-new sources of customers while increasing sales from existing customers
- Gain a 360-degree customer viw to create personalized client experiences
- Compress the product development cycle
- Reduce operational expenses
With the strong emphasis on digital transformation, it is only natural that organizations will be more focused on capturing and utilizing data to accomplish their digital transformation goals. As such in 2020 we expect that organizations will significantly augment their DataOps methodologies – technologies, enterprise culture, and philosophies that are aimed at enhancing enterprise data management in the AI era.
Data Latency Takes Centre Stage
With the implementation of 5G and increasing emphasis on IoT technologies in the region, the amount of data organizations will be dealing with will be monumental.
As both the variety and volume of data increases, edge computing will likely gain ground and even perhaps become a necessity for enterprises in APAC. Processing data centrally on-premises or in the cloud simply will likely no longer be enough to get all that data processed fast enough for impactful decisions to be made.
Firms are beginning to understand the power of edge computing and the applications made possible by processing raw data closer the source. With edge computing companies of all sizes will be able to obtain critical real time updates and make business decisions faster.
In addition to the greater utilisation of edge computing, over the course of 2020, businesses will look towards creating infrastructure that reduces data latency and accelerates outcomes using the following:
- Automated, Real-time Data Pipelines: To create personalized customer experiences, enable real-time AI and accelerate critical operational decision making, businesses will embrace real-time data pipelines. These pipelines unify applications and processes from transactions to analytics and infrastructure, provide more computational power, require data transfer improvements and enable real-time analytics applications that impact all areas of business.
- Self-Healing Capabilities: Relying on human intervention to triage job failures with real-time data flow and applications is a massive challenge. More and more, business will look to DataOps capabilities that utilize AI throughout their infrastructure that can self-heal data streams. As a result, systems and analytics will be able to self-correct without the need for human intervention.
- Artificial Intelligence (including machine- and deep-learning): Reliance will grow due to AI’s ability to make massive computations, understand language and identify image and pattern recognition across all forms of data (voice, image, text, numeric, etc.) at a rate that far exceeds the human capabilities. ML-specific investments will grow in an effort to further accelerate the decision-making process and free teams to focus on speed to market, compressing strategic planning process, product development, shortening sales cycle and more.
- In-Memory Databases and Distributed Architecture: With data coming from billions of mobile phones, endless streams of online applications and more, there will be increased adoption of in-memory databases and distributed architecture that can capture the data at its source and ensure insights are recorded in the right place.
The Democratization of Data and Push Down Decision Making
This commitment to speed won’t be addressed solely through a technological lens.
New cultural models will also gain traction including the “Democratization of Data.” This represents a profound transformation that will require proactive change management, new skillsets and processes and here’s why.
In the age of data democratization, leadership must remove traditional data gate keepers so valuable and actional new insights can flow freely to employees across all functions.
As a result, employees are becoming more informed. This new model also enables “push down decision making,” where once again management relinquishes some control to employees, including those at the edge who are face-to-face with customers, partners and other key stakeholders. As a result, employees have a newfound freedom to make critical, data-based decisions in the moment that allow the business impact to be felt more quickly.
Increased Focus on Security & Governance
Naturally, the scenarios above create new challenges, especially as global privacy and security regulatory requirements, standards and controls, and the need for additional security measures increase significantly and continue to evolve. Most recently Indonesia, announced new regulations for the country’s e-commerce industry for example.
Looking ahead, company boards will play a much bigger role in helping secure their data reputation. Specifically, boards will demand businesses have a clear data strategy and compliance program as well as the necessary controls in place around security, data privacy and data ethics. Businesses that onboard new solutions and align with these areas will be able to:
- Protect each piece of data from a growing number of threats
- Ensure data is being used ethically
- Enabling data to flow freely within the business to fuel agile decisions
- All while meeting key data governance requirements
In 2020, a business’s data reputation will create a truly sustainable competitive advantage. But success will require a commitment to new innovations and cultural practices.