How Data & Analytics Leaders should expand value while managing cost and risk.
17 March, 2022
Chief Sales Officer, Sales and Marketing,
“Data & Analytics Leaders Must Expand Value While Managing Cost and Risk’’
In a recent article, Gartner stated that the focus on Data & Analytics Leaders is becoming increasingly intense.
Firstly, digital transformation is putting them under pressure to increase business value, reduce costs and mitigate risk. Gartner states that achieving these aims is reliant on improving business relationships within the organisation, while at the same time, developing a data-driven culture across the organisation. To do this well, they must manage multiple business priorities whilst delivering solid data governance and consistent data & analytics (D&A) quality. In addition to this, D&A competencies need to be increased within their organisations and solutions, products and processes need to be increasingly data-driven.
Secondly, data monetisation, the process of increasing the economic value of data, is being realised faster than ever before in commercial enterprises. In the public sector, organisations are looking to achieve similar success through monetising data within smart cities and open-data initiatives that release value to their citizens. Whichever sector they find themselves in, D&A leaders are expected to drive this. Accomplishing this requires a level of business acumen, specialised capabilities in product life-cycle management and a sales mindset. CDOs have to do this while navigating the concerns of many people about how both public and private organisations use their data.
Thirdly, the journey to the cloud continues to place demands on data leaders to demonstrate a return on investment and provide innovative and transparent information that’s accessible right across the business. Increased automation (which enables further cost-saving) is dependent on edge technologies such as artificial intelligence and machine learning, which must be deployed and governed appropriately.
Leading the Way
The COVID-19 pandemic has increased digital transformation and modernisation efforts and thus, centralised the CDO’s role in businesses. Organisations have realised their need to become data-driven so that they can utilise data to drive growth and cost optimisation. Gartner stated this shift has driven ‘unprecedented levels of demand for D&A in decision-making.’
In doing this, they state, CDOs must continuously deliver on multiple fronts: ‘This expanded scope of value generation, cost management and risk mitigation puts the CDO in a central position, but one that is extremely challenging…CDOs must continue to deliver on digital transformation while expanding value streams, managing costs and carrying out risk mitigation.’
Achieving these objectives requires effective collaboration across different business units, which CDOs must drive. CDOs responsible for data migrations to the cloud must also work with CFOs to ensure this is done in a way that maintains value.
The successful and savvy CDO will juggle multiple priorities and turn risk into opportunity by expanding partnerships across the organisation and forming communities of practice that accelerate value creation. CDOs must capitalise on this opportunity now, or else they will undermine the likelihood of their success.
Delivering on this ambitious set of goals will require much upskilling in the area of data analytics and broadening access to data tools. Gartner feels that CDOs and other D&A leaders must balance this against focussing on other concerns, such as ‘ethics, security, reputational impacts and competing business priorities.’ And to achieve these ambitious targets, leaders need to be very deliberate in their focus and prioritise carefully.
As data & analytics platforms move to the cloud, fundamental changes in financial governance and budget processes are required. For instance, the diversity of choice in cloud offerings and pricing models means that companies need to carefully assess what options will deliver the best value. This process of budgeting differently because of cloud computing is described by the term ‘FinOps’. In essence, FinOps is about optimising cloud spend to get the most value for the company.
Once FinOps is in place, applying Machine Learning and Artificial Intelligence to augment the FinOps process is an obvious progression. In its initial phase, Gartner states that augmented FinOps will lead to up to a 40% reduction in effort. This occurs mainly through task automation, beginning with improved monitoring and recommendations. Eventually, this moves to full-scale automation. The result should be that business users will be able to set broad, high-level objectives in natural language and have the intelligent system deliver on this for them.
These capabilities are in the early stages. But as cloud economics highlights, the only metric that genuinely matters in the cloud is price/performance. Given this, it’s only a matter of time before augmented FinOps will become an integral part of mature D&A ecosystems.
In addition to overseeing movement to the cloud, the CDO must navigate changing governance processes. For instance,
- The emergence of the data ethicist role – This new role has been created to ensure that any new value that is generated from company data matches the organisation’s own values about that data. The ethicist monitors for unforeseen consequences that may lead to excessive insights into the lives of people which may lower people’s trust in the company. The ethicist is responsible for making all stakeholders ethically aware and mitigating the company against misuse of data.
- The emergence of new governance structures – Because of the public’s interest in how businesses handle their data, companies must be able to demonstrate how they govern this data. Gartner feels that one of the best practices for doing this is conducting ethical reviews. This can be done by instituting a digital ethics advisory board. This should consist of people from different areas within the organisation and, on occasion, people from outside the organisation. Some organisations that do this already, discuss cases together to create institutional knowledge on how to deal with these sorts of ethical dilemmas around personal data. Some organisations that are experienced with Artificial Intelligence then test their models regularly to look for “drift” in their models.
- The emergence of new data governance technologies – Although technology cannot solve digital ethics, there are areas where it can contribute. In the field of AI, many technologies emerge that help with bias detection. And in the field of privacy protection, AI assists with privacy-enhancing computation (PEC) techniques, including approaches such as contextual privacy and differential privacy.
CDOs and other D&A leaders have an increasingly complex role. The focus on the role of the CDO is unlikely to change in the immediate future as businesses pursue the goal of becoming truly data-driven and all the benefits that results in. This will require CDOs to rise up to the challenge and take advantage of the opportunity this affords them.
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