Designing a data strategy to leapfrog the competition
Ask any CEO what keeps them awake at night and most will point to their growth, profitability or staying ahead of the competition.
Exploiting data and technology appropriately can create that competitive advantage, especially with advancements in storage and computational power. But the reality is that organisations and leaders at the cusp of a data journey still rarely know where to begin and how to lead successfully.
A winning data strategy
A strategy is about choices – knowing what to do and crucially what not to and why. Understanding the ‘why’ behind data requires tough introspection, in addition to an understanding of the strategic context and business environment.
Firms embarking on this process must assess their ambitions for growth and the role data will play in it – lead or enable. Traditional businesses will often choose paths where different sources of data can enable their value propositions. Whether it is customer data to understand detailed segmentation and offer personalisation, or in-software telemetry used by product development teams to design and improve customer experience journeys.
However, the true opportunity lies in the ability to unlock new propositions and business models that enable the monetisation of data assets. Forex companies offering APIs so accounting software providers can access real-time data for travel and expenses submissions, for example.
Organisations looking further into the future to get ahead ought to consider how data will become core to their proposition, as opposed to simply enabling it.
Use Cases: A vehicle to ground the strategy in reality
Too often, strategies risk becoming disconnected from the harsh realities of execution. Stories of ill-conceived investments that did not pay off, along with boil-the-ocean data projects that are not value-focussed are a common occurrence.
One of our clients was led to believe a data strategy is an organisation design effort to build a business intelligence capability. However, they were unaware of how data would add value to their proposition, opening the door to significant investments with unsatisfactory results.
This highlights why a good data strategy needs proof-points in the business to translate into successful execution. Though big picture considerations by decision-makers are important, the best way to start a data journey is with use cases that bring the strategy to life.
Use cases are a proving ground for both technology and data practices to be tested and rapidly learnt from to establish a high-performance operational capability. They help to put the data strategy into effect with best-in-class data science techniques used to address real problems and deliver outcomes, while also testing the strategy in-flight.
Promoting a data-driven mindset
Being data-led is a means to unlock the potential in data. We cannot ignore that a well-executed strategy will drive a fundamental shift in an organisation’s people, processes and practices.
However, implementation needs to cater to the differences in learning and adoption curves presented when deploying use cases across different user groups. Some skilled practitioners will have their years of experience, methods and approaches challenged by data and decision-support tools.
Without careful consideration, entire sections of a business may reject the ideas, risking the successful creation of a data-driven mindset.
The secret to success
There are emerging schools of thought on valuing data as an intangible asset, owing to the enormous promise it holds. However, as will be the case in several businesses, untapped, underperforming, or nonperforming assets do not have much value.
Also, a business must resist the urge to follow suit and copy a competitor’s approach. No two organisations are the same, especially when it comes to how data can drive value.
A well-thought-through data strategy can prevent missteps that sap confidence in data initiatives. In combination with the execution of use cases to build a data-driven mindset, it will unlock the true potential of data.
The secret to success lies in starting with the ‘why’ (strategy), before making choices on the ‘what’ and the ‘how’ (data capabilities, standards, operations, governance).
More in insights...