Modern businesses are under pressure to offer a superlative customer experience to stand out from the competition. This can only be achieved by developing a keen understanding of the customer, which requires making effective use of the unprecedented volumes of user data being generated and stored.
Cloud-based analytic tools, artificial intelligence (AI), machine learning (ML), spreadsheets, and other technologies allow organisations to extract competitive insights from the massive amount of data companies collect and acquire.
A recent report from the Economist Intelligence Unit (The EIU) says in a knowledge-based economy, the ability to generate data-driven insights will align more and more with companies' overall competitiveness. More than two-thirds of companies that the EIU surveyed in 2018 said their profitability had increased over the past three years thanks to their digital strategy and nearly three-quarters expect it to rise in the next three years.
But while the rate at which businesses produce data is growing exponentially, the rate at which companies are able to use this data productively is lagging. Organisations risk being buried under too much data. Bridging this gap is key to unlocking the true value of data and transforming the customers' experience.
Forging a data driven organisation
Companies that have made the most progress overcoming this gap have adopted a data-first strategy that permeates their entire organisation, and allows them to deliver the stand-out customer experiences that are driving their growth.
This requires creating data management platforms capable of reliably collecting data, finding patterns and trends, and providing insights that inform better strategic decisions. It also means transforming into an organisation that values data at its core, which could involve retraining employees or placing responsibility for data further up the chain of command.
Linking data strategy to business strategy
Arguably the first step in forging a data driven organisation is ensuring that data collection and analytics strategies are aligned with key business objectives, such as improving sales and profitability, enhancing product quality and efficiency, and improving the customer experience.
This last objective has become a key focus of companies seeking to complete this journey. Indeed, the ability to collect and utilise vast volumes of data is giving enterprises an unprecedented ability to gain deep insights into the customer experience and anticipate their needs.
For example, some organisations are focusing, in minute detail, on the speed with which individuals click through their websites, to determine and address pain points in the user experience. Others are using this data to continually refine AI chatbots capable of responding to increasingly complex requests.
Improving and maintaining the quality of data
Another requirement is ensuring that the data used in decision-making is of sufficient quality to deliver actionable insights for improving the customer experience. This means designing systems, processes, and data architectures capable of consolidating and cleaning data and presenting it in a usable form.
It also often involves collecting data from multiple sources. An effective data management platform will be capable of integrating a company's own data with that of second-party partners and third-party external data providers to maximise the insights that can be derived.
To ensure compliance with privacy, data residency and other policies and legislation, it is also essential to implement a strategy that involves anonymising data before making use of it in analytics.
Gaining agility by enhancing visibility into data
A common stumbling block many organisations are facing in their efforts to become data-driven is a lack of control or visibility into data. Often the sources called on are distributed throughout their operations and on public and private clouds.
In fact, The EIU's research found that 55% of business leaders worry they are not making optimal use of data and digital technologies within their organisation. Effectively utilising distributed data requires transferring data into a coherent repository, overseen by a master data management (MDM) tool for consistent, secure use.
Companies are increasingly choosing to keep structured data in a data warehouse and moving unstructured data to data lakes on the cloud. Flexibility and low storage costs mean that organisations can keep a much larger volume of data than in a traditional relational database.
Paving the way for revenue digitalisation
The survey conducted by The EIU for its report found that nearly three-quarters of companies expect the effective use of data to have an increasing impact on their profitability over the next three years.
Oracle's own research found that 66% of organisations are using at least one emerging technology, such as AI, intelligent voice assistants or Internet of Things (IoT) devices, to augment the customer experience.
Among those using at least two of these technologies, more than seven in 10 reported that in excess of 10% their revenue is being derived from new digital offerings -- nearly double the percentage of businesses that have not embraced emerging technologies for improving the customer experience.
Oracle can guide you on your journey
Although joining the ranks of these high achievers may seem daunting, the good news is that adopting a data-first strategy need not be either difficult or expensive. With Oracle Autonomous Database, customers uniquely get the world's leading database, Oracle Database, on the best platform, Exadata. This combination provides the most secure, available, performant, proven solution at the lowest cost as all operational tasks are fully automated with embedded machine learning and customers only pay for resources they use.
The Autonomous Database's fault-tolerant scale-out cluster that works transparently for both OLTP and Analytic workloads makes it uniquely capable of running Mission Critical workloads. The Autonomous Database is also the safest cloud deployment because data is automatically encrypted, and security updates are automatically applied as soon as they are available. It guarantees 99.995% uptime, including planned maintenance activities. It has the simplest, quickest, and safest migration with fastest time-to-value because customers can easily migrate their existing databases to an Autonomous Database in either the Public Cloud or Cloud at customer environments without needing to make any changes to their application.
Use case: Acting on the insights to improve experiences for prospects and customers
In a demonstration of the ways data can help shape customer experience, leading companies are increasingly using data and AI to offer hyper-personalised, omni-channel, connected experiences.
By applying adaptive intelligence, organisations are finding they can bring together disparate data sources to build a single view of their customers and prospects, capable of delivering deep insight into digital profiles and behaviour.
As represented in the figure above, insights gained from data can be used to deliver the personalised experiences customers have come to demand.
Oracle helps organisations use data to manage their digital experiences for prospects and customers.
Co-authored by Brian Wylie, Key Account Director for CK Hutchison Group and Arul Ganeswaran, Global Client Advisor.