What drives digital transformation: Tips for chief data officers
Digital transformation can mean an array of different things to people, depending on your industry and the nature of your business. Ultimately, a digital strategy must focus on improving business processes and outcomes, like offering new digital products or increasing your customer engagement.
The means to that end lies in how firms improve the management of their data. This puts the chief data officer (CDO) front and center as companies digitally transform.
Along those lines, below are some tips that can help guide companies through the data strategy that must underpin their digital transformations.
It’s all in the cloud, so take advantage
From a data management perspective, cloud architectures offer a variety of features – from multi-tenancy to content delivery networks – that enable easier access, re-use, and distribution of data. This can power software-defined automation as well as new DevOps approaches. Enabling the agile digital business to innovate, test, and scale quickly, while offering continuous uptime.
Business model disruptors: artificial intelligence and machine learning
By facilitating processes, such as natural language processing, image and speech recognition, AI and ML have begun to automate tasks that previously could only have been performed by humans. Customer-facing applications, such as Alexa, Google, Siri, and Cortana, achieve most instant-recognition, however, there is a myriad of use cases where AI/ML is used in the background to automate complex and/or large-scale data processing. Everything from automating insurance claims and optimizing financial models, to performing medical diagnoses.
It’s vital that organizations using AI and ML techniques to ensure tight oversight and an understanding of the data and logic underpinning that analysis. While neural networks were traditionally black boxes, the transparency of AI/ML decision-making is beginning to improve, which will be vital to support increased adoption.
Ensure the data you generate from IoT is robust and secure
The proliferation of data-gathering devices will provide an explosion of data to analyze, interpret, and ultimately guide business decisions–be prepared to manage this.
Just as IoT covers a wide variety of use cases, it also poses a broad range of data management challenges. One of the primary considerations should, therefore, be around how to ensure things are protected from hackers. Equally, because of the distributed nature of some devices, network bandwidth considerations and communication protocols need to be properly evaluated.
Why “data ethics” is more than just compliance
At the very least, organizations will need to satisfy existing regulations relating to data privacy, which for multi-nationals involves complying with a complex matrix of obligations affecting different jurisdictions.
Beyond that bare minimum, client consent and transparency have emerged as critical considerations for companies. Customers are more likely to provide consent to organizations that they trust. They are also more likely to trust organizations when they can actually perceive the value they will receive by providing that consent. For example, modern digital titans have been able to add value by modeling users’ behavior to present them with more relevant product recommendations, useful advertising or viewing suggestions.
In other cases, digitally native companies such as with Airbnb and Uber have used data and technology to connect new sources of supply (people’s spare rooms or those who want to earn money by providing rides) with demand for those services.
While demonstrating value is paramount to building trust and eliciting consent, breaches of trust can occur quickly and bring potentially adverse outcomes. This is a theme that will only continue to gain momentum in our modern era.
It’s the CDO’s responsibility to invoke company-wide change
True digital transformation requires cooperation from across the entire organization. A single person may be charged with defining a company’s digital strategy, but it’ll take agreement from across the organization to execute against that strategy.
Many digital transformation projects require organizations to break down data silos, which in turn will require support from business units that own those silos. Others may require setting up new businesses and/or adopting new practices, which could be seen as threats to established operations if not handled carefully. CDOs must do more than simply sprinkle data and analytics over an existing organizational structure.
The competitive forces of digital transformation have been in motion for some time. Firms that view data as an asset will inevitably be better at mining, refining and extracting value from it. In doing so, they’ll discover innovative ways to optimize business processes and deliver value to their customers. In turn, as customers begin to expect more from their product/service providers, they’ll become more discerning with their purchasing decisions. Staying still is therefore no longer an option.
But in order to be effective, technology needs to be supported by the right individual and process. As firms seek to unlock their data assets, they’ll encounter numerous governance challenges. Who owns the data? Where is it stored? Is access properly controlled? Are there restrictions on its use? All these questions need to be answered in tandem with the key commercial imperative: how can I make use of data to add value to my business and better serve my customers?