Liberating data: the new paradigm to drive business success and customer delight

Welcome to this three part podcast series on ‘Liberating data: the new paradigm to drive business success and customer delight’ brought to you by Google Cloud, Accenture and Foundry In this our first episode we’ll be talking about the importance of developing a proper customer data architecture (CDA) as the first step towards truly realising the potential of your business data to help transform customer experiences. In today’s hyper-connected, 24/7 digital world customers are demanding everything from faster delivery to more choice as well as greater levels of personalisation than anyone would have thought possible even just a few years ago. Yet, as Accenture’s marketing and customer experience lead, Rajiv Mohan notes, a recent study by the firm revealed that while 80 percent of firms think they’re doing a great job delivering better customer experiences, only 8 percent of customers agree with them. In order to delight and retain customers, all organisations – especially those that are heavily consumer-facing – must leverage integrated customer and enterprise data to enable real-time, audience centric marketing and personalisation across channels. It also means breaking down silos, in particular those separating customer / sales data from marketing data. As Rupert Farrow, head of advanced data partnerships with Google APAC explains, the growing number of organisations that might be described as digitally native have a natural advantage, especially in having fully integrated channels, which makes them better placed to deliver better customer experiences. He adds that while all companies are now being urged to become data-led digital businesses, the guardrails for doing so have become narrower – and higher – with governments and law makers moving to guarantee personal privacy as the number and severity of data breaches continues to increase, along with the repercussions. In effect, today’s organisations have two very important objectives that appear to be at odds with each other: learn as much about their customers as possible to enhance their experiences, yet while ensuring they don’t spill a drop from their large and growing data lakes – or silos – while doing so. For many digitally-native businesses, the task of both revealing and protecting customers at the same time is baked into their DNA. Yet for older more traditional businesses, evolving to become truly data led requires a complete rethink of their technology stack.

Welcome to the third and final episode of this three part series on ‘Liberating data: the new paradigm to drive business success and customer delight’, brought to you by Google Cloud, Accenture and Foundry. In the previous two episodes you will have heard the case being made regarding the immediate need for today’s organisations - of all type and size – to re-examine how they capture, store and utilize data to meeting the growing demands of customers in today’s digital world. As we heard in episode one, it all starts with building the right customer data architecture (CDA) as the first step in developing systems and processes that enhance the customer experience, at the same time as protecting their privacy and security amid a fast evolving regulatory and compliance environment. And as cyber villains continue to stay ahead of law enforcement. In episode two we talked about the challenges of data swamps masquerading as data lakes, and further explored the need for organisations to shift their mindset to find sensible and smaller scale use cases to get started, as well as promoting the broader use of data tools across their entire organisation. We all now know these are among the key traits of so-called ‘digitally native’ organisations, which all businesses need to adopt if they are to remain competitive and relevant. And contrary to critics of AI and ML who warn against the technologies’ potential to take jobs from people, successful digitally native organisations show how they can be applied to automate and speed up tasks, augmenting human endeavour and freeing time for more meaningful activities. In this episode we’ll be discussing modern AI applications and accelerators and how best to extract meaningful insights from your data sets to drive better business outcomes. Vaughn Muirhead, associate director Cloud First, with Accenture’s Google Business group, stresses that AI and ML shouldn’t be thought of as magical and complex, only to be handled by trained data scientists. These and other advanced data tools have evolved to become much easier to use, he adds, calling for a genuine “democratisation” if organisations are going to extract the most value from their data to advance and stay competitive. And Andrew Psaltis, technology practice lead, data analytics and AI/ML with Google Cloud APAC, says that one of the most important trends that organisations should take greater heed of is that customers are becoming much more technology and data-driven themselves, offering music streaming service Spotify as one of many examples.

Welcome to second episode of this three part series on ‘Liberating data: the new paradigm to drive business success and customer delight’ brought to you by Google Cloud, Accenture and Foundry. In episode one we heard about the importance of creating a proper Customer Data Architecture (CDA) as the foundation stone to gain greater clarity of what data exist and where, and to start bringing them together. In this episode we’ll be exploring the topic of ‘Liberating legacy data through data digital decoupling’. Doubtless there are many CIOs out there feeling overwhelmed by the volumes of enterprise, customer and other sorts of business data sitting within on-premise legacy systems. But it’s imperative that they start down this path of ‘liberation’ ASAP in order to deliver the sorts of customer experiences now universally expected of them, and in many cases likely already being delivered by their more advanced competitors. Russell Nash, customer engineer for data analytics at Google Cloud, says trying to use AI without data “is liking trying to make an omelette without eggs”. Customers he speaks to feel a lot of disappointment at the returns they’ve achieved with their existing data investments, as well as frustration with the complexity involved in standing up workable AI and ML models, even with highly trained data scientists on the job. And Amit Vilecha, Google solutions architect with Accenture notes there are many, many organisations still with huge volumes of data still on premise, including data trapped within older legacy systems. Yet organisations need to understand it’s not so simple as just “modernising” and moving everything to the cloud. He adds many companies have developed expansive – and expensive – “data lake” architectures with all the right intentions, when in reality what they really have is better described as “data swamps." They know there’s enormous value trapped within these vast repositories of legacy data, but likely don’t have a clear path for extracting it effectively and integrating it with their evolving digital systems.