By Gary Richardson, Managing Director, Data and Emerging Technology, 6point6
With another year under our belts, and an even heftier investment figure, companies who’ve poured millions into digital transformation projects will once again feel saddled with disappointment that the hype of shiny new technologies falls short of their grandeur promises.
With many executives having expressed concern over ‘game-changing’ technologies, many of the failures have become a crucial lesson in sustainable implementation. With this fresh in the minds of companies heading into 2020, we will begin to see a widespread return to getting the fundamental basics right to ensure the digitalisation of business can operate at scale without compromising stability, and quality.
Enter DataOps – a set of agile tactics designed to support and streamline AI, data analytics and machine learning initiatives. To make more intelligent and strategic use of data, actionable insights across the entire business pipeline must be consistently realized to paint an accurate picture of execution, and adapted accordingly. In 2020, DataOps will bring much needed respite to businesses where disillusionment runs rife. Here, we breakdown why and how DataOps will pave the way for success.
Dirty data is no longer an option
Data’s status in financial services has grown more prominent as emerging technology initiatives move from proof of concept to live in real-time. The hygiene and care of data up and downstream is becoming a normal course of business. To do it right, data quality and governance must be front and centre to ensure they are consistently aligned with business objectives. The alternative – poor and insufficient data – can leave digital transformation projects dead in the water.
Not only can dirty data hamper the progress of digital projects, it can even wreak havoc on regulatory requirements and create sub-optimal business strategies. That is why data hygiene is of paramount importance. While there are various platforms available to carry out large scale data cleaning, the fatal mistake companies are learning to avoid is the failure to implement a data culture. As with any advanced tool, its users’ understanding of how to apply it to business objectives will determine its success or downfall.
Introducing a DataOps function not only helps firms to mature their data-cleansing processes, meaning all data produced can be analysed and applied elsewhere in the business pipeline. It allows people across large enterprises to truly access the potential of data.
A data culture is the key to the kingdom
DataOps is designed to greaten the understanding of the data journey across enterprise. The aim is to ensure everyone, from data scientists to business operations, can extract and master the information for the business’ advantage.
As more processes go digital, a dynamic cross-team approach to analytics will allow firms to generate a better picture of data assets. A DataOps function will act like a steward, providing the guidelines for cross-functional teams to focus on short and long term strategy and data literacy; ultimately enabling data to flow seamlessly across a business. This creates a culture whereby everyone is working towards a common goal closely aligned to the objectives of each pipeline.
The true value of any digital transformation project can only be unlocked when the data is refined throughout the organisation. If the data is mishandled or misunderstood by any team member at any touchpoint, then the most meaningful insights can be lost.
Without strategic deployment of a DataOps culture, silos and isolated pockets of disconnected information will continue to disrupt productivity and growth. Businesses looking to establish themselves as data-driven who ignore the crucial ingredients of DataOps will fail to access the benefits of a more complete, holistic and accurate view of data.
Once a company embraces the principles of DataOps, the road to more robust operational resilience is clearer. Maintaining the security of data systems has never been more important and it deserves its place as a priority.
DataOps: a proactive approach to operational resilience
Companies have learnt that the pursuit of short-term financial goals combined with rushed ‘lift and ship’ data platforms ultimately mean projects become obsolete before completion. DataOps provides a framework where resilience is met through a combination of strategic planning and proactive measures put in place to tackle challenges before they’ve occurred. As we’ve learned the hard way, it is much more cost-effective to solve an issue at the design stage of the life cycle rather than later down the line.
DataOps encourages firms to bring each team together to leverage data to assess the full lifecycle. From design, build to system maintenance, DataOps embeds the connective tissue throughout to ensure that the deployed capability is and continues to be resilient while avoiding any critical platform failures. This can and should be applied to any digital transformation project. Ongoing monitoring and optimisation leads to projects that will stand the test of time in an ever-changing data landscape.
Long may DataOps reign
The time for false promises and fairytales is over. It is clearer than ever that a DataOps strategy is required to enhance operational resilience and give businesses the edge to compete in today’s data-driven environment. What will really demonstrate DataOps’ ability to stand the test of time is the way in which it can be successfully applied to culture. Investment in technology is no longer enough, companies must make a valuable commitment to address the human side of data to really seize its benefits.
