Digital transformation has been hypothesized, discussed, piloted, deployed and iterated over the last few years, with each version reflecting new developments mostly around technology. But at the core of even the most recent iterations of digital transformation are the same core technologies: advanced analytics, artificial intelligence, automation, cloud, edge computing, Internet of Things, and machine learning.
There are two misconnects in how organisations envision and deploy technologies under the guise of digital transformation: one solution meets the needs of all businesses; technology needs to be constantly refreshed to benefit from advances.
For example, automation can help reduce errors, improve efficiency in many processes. While the underlying principle is universal, not all processes can, need and should be automated, and even similar concepts like workflow automation are different for different industries. The morale here is no one technology can solve everyone’s problems.
Daniel Gunawan, Managing Director – Intelligent Software Engineering Services – ASEAN, Accenture, pointed a corollary to this: there is no one-size-fits-all solution.
The task for the CIO and the IT team is to understand the business requirements, review the position they are in from the standpoint of technology currently in use and skillsets available internally and externally, and plot a strategy that sees the company adopt a complex interconnected “living” systems of technologies, applications and people.
Accenture alludes to enterprises as living businesses that evolve in response to changes in the socio-economic environment, where investments in technology are seconded to the businesses’ core goals.
For instance, a common goal for many businesses pursuing a digital transformation initiative today is customer-centricity. To achieve this goal, however, the business must be able to draw sufficient data about the customer, potentially from multiple sources inside and outside the organisation, and match the customer’s needs to the company’s product offerings.
Such a business model could potentially require massive infrastructure covering servers, storage and connectivity to house not only the applications, data and storage needed to analyse the data to deliver what many customer-facing businesses like retail, telecom, and healthcare, desire – insight to deliver the “mass personalisation of one”.
Gunawan illustrates this example with Cathay Pacific’s Asia Miles loyalty programme. The final solution co-developed with Accenture brought together blockchain, micro services and cloud technology that addressed three key targets: allow AsiaMiles members to manage their accounts in real-time, use blockchain to eliminate merchant waiting time for data, and reduce costs and administrative provider tasks for data collection and payment.
In this exclusive interview with FutureCIO, Gunawan describes the business value of building a living systems architecture that uses proven technologies like that of AWS cloud technology with emerging technologies like blockchain to enable business models.
Asked whether what organisations need to future-proof their technology investments, Gunawan suggested that enterprises first understand where they are at in the maturity of their technology adoption, identify the innovation gaps that they need to fulfil, then look to technologies like cloud and automation to embark on this process.
