Seamless integration of data and analytics with standard operations should be the goal of all organisations targeting real business value, aligning both IT and the C-suite in key roles.
To achieve this, however, our CIO and IT Leadership Survey 2020 finds only a quarter of large organisations electing to install a chief data officer (CDO), and 16% of the senior IT and data lead executives we surveyed indicating a lack of skills is impeding their data strategy. This is at a time when the market trend is to bring key skills back in-house.
Indeed, the survey results highlight many obstacles for companies to overcome before they see meaningful benefits at scale from their data through the technology-led investments that will drive future growth - from natural language processing (NLP), robotic process automation (RPA) and machine learning to artificial intelligence (AI).
Only about a third (34%) confirm they even have a centralised and seamless view of all their data - typically a foundational step needed to drive widespread adoption of machine learning or other analytics-focused implementations[i].
However, of the top five enterprise data bugbears in our survey, the majority are business-related. It's not just about the difficulties that come with the scale and complexity of data sets or integrating new technologies, but the lack of a data operations model, issues with governance and ownership of data, and achieving or maintaining regulatory compliance.
Additionally, nearly every type of business is experiencing disruption by new players, coupled with less customer loyalty than they would like, especially on new digital channels. Instead, organisations could be using digital disruption and transformation as a springboard for investing in the customer insights and new product development that will help them expand.
It's the businesses themselves that are set to benefit from correctly prioritising resources to integrate data management and analytics. 74% of organisations in our survey acknowledge that data is a critical business priority.
Why then do 80% appear to see data accountability and management as a technology problem? Respondents to our survey indicate they believe data accountability in their organisations rests with technology leaders such as IT directors, CIOs or CTOs. Organisations could effectively be setting their digital transformations up to fail as they struggle to extract real business value from their data through analytics-based insights.
Emphasis is put on speed, cost, and competition, while the more fundamental transformational business value is overlooked. Quantitative product development, predictive customer insights, intelligent automation and a singular focus on value-added activities are just a few of the prizes for the analytics-focused organisation, but these are not being prioritised[ii].
Yet our survey also suggests that many large organisations ultimately desire to implement and benefit from these advanced capabilities.[iii]
What then is the answer?
Clearly, organisations that are aiming for successful analytics implementations in future should be looking today at how and when to skill up. Nearly 60% of respondents indicated that they will hire new in-house staff within next three years.
Our research suggests, however, too much focus on IT skills, without consideration of how to develop the appropriate senior roles to ensure joined-up thinking right up a business 'stack'. Effective data developments cannot and must not be siloed, but connected to ensure that all working parts act together to deliver business value.
This advocates the need for education across the C-Suite, and around the role of the CDO should this be the direction selected, which may prove valuable at least in the medium term to many organisations to drive behavioural and organisational changes needed.
This will all of course take time. While we are seeing companies investing in foundational skills and looking to move these skills in-house and introduce new roles, third parties and external contractors will continue to play a key role in filling the required data and business skills gaps[iv].