Data is growing faster than any organisation can keep up. At the same time, organisations are also faced with rising customer expectations, unprecedented natural disasters, and complex macro environments.
Today, there is a sense of urgency for organisations to relook at and redefine business models to be more resilient to volatility. Innovation is no longer just experimental but focused on cost optimisation, creatively searching for ways to achieve a high return on investment and lower the total cost of ownership.
Hence, organisations are looking at solutions, such as data optimisation and innovation, to help increase productivity while generating more significant value and output with the same input. Additionally, organisations need to reconsider the roles of three key areas: Technology, process, and people, to achieve tremendous success in data optimisation and innovation.
Using technology to drive better business processes
Based on Splunk’s Economic Impact of Data Innovation 2023 report, 85% of organisations in Singapore rated the importance of uncovering and better operationalising data as one of their top 10 priorities. More than three-fifths (65%) of them shared that data has helped them make better decisions faster than their peers.
To better operationalise data, organisations in Asia Pacific have adopted three mature technologies to support their data innovation. The first would be the use of public/ multi-cloud, which helps them accelerate time-to-market, reduce complexity, and drives standardisation within business units.
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The second is end-to-end observability which helps improve customer experience, increase release velocity, and reduce system downtime, leading to positive customer experience and less monetary loss.
The unification of data platforms also helps streamline operations and simplify processes that help optimise cost. Global leaders get 2.3 times as much revenue from data monetisation. However, with such excellent prospects that data has to offer, Singapore companies are lagging, with 34% facing inter-team data consolidation issues, preventing them from advancing an idea.
Due to the lack of relevant talent, 37% shared that the data generated did not have the quality or format to support innovation practices. Tech solutions, such as using artificial intelligence to drive automation or hyper-automation, could potentially remedy the challenges Singapore organisations face when it comes to democratising data.
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The strategic approach to processes in driving data innovation
To solve data problems is to understand them better. A few essential points highlighted in the same report showed how leading organisations are implementing processes that prioritise data optimisation or innovation, earning them significant measurable positive outcomes.
Other critical strategies highlighted in the report that could help organisations drive innovation include:
- The prioritisation of data innovation: The majority (85%) of organisations in Singapore rated the importance of uncovering and better operationalising data as one of their top 10 priorities. Nearly two-thirds (65%) shared that data has helped them make better decisions faster than their peers.
- Invest in places that help make money: Data innovation leaders allocate 53% more of their technology budgets for solutions and staff aimed at data investigation, monitoring and analysis than beginners. For example, 15% of organisations in Singapore have taken steps toward training and nurturing talents that help drive data innovation.
- Look out for disruptive competition: Organisations need to go beyond their industry competitors and listen to what the data shows. Sixty-nine per cent of leaders predict that data will trigger a significant change in the goods and services their industry provides, versus 65% of intermediates and 47% of beginners.
The total disposable income for the Asia Pacific region is set to more than double in real terms over 2021 to 2040, faster than in any other region. Some of the major growth drivers include rapid economic development, ongoing urbanisation, and growing digital adoption that has created an upswing in digital platforms such as e-commerce.
It is no surprise that the retail sector can be seen leveraging data more than its peers to drive their business by elevating shopping experiences, from streamlining internal processes and supporting the increase in online transactions to addressing customer queries to support sales.
For example, CAINZ corporation — a home improvement retailer with over 220 stores in Japan — needed to monitor its e-commerce operations and website performance across various microservices in a multi-cloud architecture. The transition to a multi-cloud environment complicated monitoring front-end performance since the different web service platforms supported everything from settlement functions to inventory and member information.
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With the help of Splunk’s data-driven observability platform that helped to transform data into real-time actionable insights, CAINZ was able to streamline service monitoring and accelerate issue detections — leading to an eightfold improvement in performance.
The alchemists in the world of data innovation
Now we know how data innovation and optimisation can help organisations, but who are the people who will help steer the wheel and drive the process?
For organisations in the Asia Pacific, the top three roles that could help drive data innovation in organisations would include the likes of cloud architects, software engineers or site reliability engineers (SREs) and data scientists and machine learning experts.
Cloud architects help organisations plan and execute their cloud journey by lifting and shifting applications to public and hybrid cloud environments. SREs help the business understand the user’s needs and develop solutions to make life easier for their intended audience. Lastly, data and machine learning experts who can identify crucial data points across business functions also help organisations make better-informed decisions.
The ultimate goal for organisations is to work towards data monetisation. Data leaders are 5.5 times as likely to say data boosts sales win rates by 10%. Properly collected data can help with accurate decision-making for innovative initiatives, from critical improvement to increasing productivity — driving business and economic growth.
Business stagnation can be detrimental to any operation. Investing in relevant innovation and processes will enable organisations to be adaptable and agile and confidently ride through the economic uncertainty ahead.
Dhiraj Goklani is the vice president for Observability at Splunk APAC
