Data Transformation & ROI

With the unprecedented geopolitical situation around the globe, organisations are in a constant state of flux to make decisions on investments. Australia’s willingness to invest in quantum computing, Google’s advent in Gemini and with Microsoft’s Co-pilot experience, the potential of data and its ability to steward an organisation to bring in differentiation seems to be a no brainer. As large organisations continue to invest in data and analytics, and as the transformation journey matures, benefits realisation for these organisations may become convoluted. Smaller organisations with limited funds need to have a closer eye on managing ongoing data related operational costs along with determining the right transformation opportunities, which will help them thrive against the ever-increasing threats. With constantly changing market conditions, rising cybercrimes and rapidly growing technological advancements, it’s more important than ever for organisations to determine sustained benefits of data transformation.

Tangibles
Technological revolution spiking at a rapid pace, and as businesses try to get onto the AI bandwagon, communication of data transformation strategies needs to permeate from the topmost to the lowest levels of the organisations. Whilst data strategists articulate the potential outcomes from data initiatives, often the business processes to imbibe these may not have been thought through. This may lead to the rate of adoption of initiatives taking a long time, in turn leading to lost opportunities for the business to gain competitive advantage.

Large organisations are at an advantage due to the appetite of investments. These organisations may therefore be able to scale-up data teams quickly, leveraging both their own talent and vendor talent. Often returns of these investments may come at a higher cost due to value being measured over a period of multiple years, outcomes of initiatives scoped out for few business units and decentralised data teams. Whilst transformation initiatives may begin with the launch of new technologies, horizons for immediate value versus long-term benefits may need articulation in terms of people and processes.

Execution of initiatives providing long-term value may have a good return on investment if the transformation strategy is nimble and can be constantly realigned to business objectives. Hypotheses testing and pilot projects provide the benefits to determine the likelihood of the transformation’s success along with the creation of a roadmap to scale initiatives widely, bringing in further certainty for investments. If data transformation strategy does not have enough levers and the roadmap is inflexible, costs of investment may be high with limited potential returns.

Often with organisations, data transformation vision may be limited to the leadership team at the top, and communication to squads may be limited or on a need-to-know basis. Whilst this may be essential in some scenarios, sharing the strategy with execution teams is necessary to enable team alignment. This brings in diverse perspectives and motivates people to contribute beyond their usual skillsets, in turn leading to faster outcomes.

With rising inflation and economic uncertainty, it’s critical for organisations to review investments on a quarterly basis and realign spends.

Intangibles
Whilst return-on-investment focusses on monetary benefits, it also involves shifting mindsets from working in autopilot mode to thinking in innovative ways. Supporting creativity and seeking perspectives during transformation leads to a spike in employee motivation. As people notice an uplift in skills, this then permeates across multiple business areas, leading to further support of data transformation initiatives and increased likelihood of investments.

Successful data transformations have change management and cultural uplift at their heart. People need to be onboard way before transformation is underway. Establishment of data-driven culture needs change agents across the organisation to review the current maturity and shift it over time to new ways of working.

Increased revenue and efficiency, lower costs and improved productivity may be used to calculate net gains from data transformations. Many organisations measure this by the rate of adoption of new technologies, development, and leverage of new skills along with number of people who can articulate advantages of data initiatives with ease.