How to create a data-driven insight strategy

Few can dispute the importance of data. In the era of AI, data sits equally with capital and human resources as organisational assets. However, having tons of data alone doesn’t automatically signify a competitive advantage.

Today, organisations must navigate a vast sea of information from both internal and external environments, leading them to ask the questions: Are we optimising data resources? Are we proactively extracting insights to guide future action and achieve desired outcomes?

Asset-intensive industries are beginning to utilise data and artificial intelligence (AI) for decision making with the same enthusiasm as other data-driven sectors like health care, banking and insurance. Most asset-intensive industries had a much later start, owing to a lack of foundational capabilities such as technology backbones, infrastructure, and a large team of data scientists. Data-driven insights offer improvements in business operations, business models, lifecycle management of assets, and predictive maintenance.

A comprehensive data strategy enables data to be converted into quality, actionable insights that inform decision-making, inspire strategies and fuel innovation. Additionally, it represents a company’s commitment to uphold high ethical standards, security, trust and regulatory compliance. 

Two clients that partnered with GHD Digital are striving to actively harness the power of data to transform their business. A modern port and logistics business is now guided by a high-level, fit-for-purpose data and knowledge management roadmap to gain clarity across operational assets and achieve elevated standards within its network. Through a design thinking-led investigation, the port started its data and knowledge management journey with a series of stakeholder interviews and a review of key areas of information management, i.e., technical and asset information. These enabled the organisation to understand its data ecosystem, identify efficiency barriers and unlock growth opportunities.

Likewise, an infrastructure-rich water utility sought to fast-track its digital transformation; however, while some data platforms and technologies were in place, no foundational guidelines existed to ensure consistent and sustainable maturity. In partnership with our global innovation practice, the organisation embarked on a collaborative design process to build a digital framework and guiding principles to support their digital strategy for the management of its water infrastructure namely stormwater, drinking water and wastewater, and connect it to the organisation’s objectives. 

When you look at your organisation’s immense pool of data, determining what to do with it can be overwhelming. This is a common scenario; not knowing where and how to start a data strategy can compel organisations to delay it or begin the journey well-intentioned but misdirected.

Here, we’ve outlined steps to design an impactful data strategy that can yield favourable outcomes:

1. Check whether your company has a data strategy. If so, assess its relevance in line with organisational objectives and possible uses. Update it accordingly to ensure that it still serves its role and that the parameters apply in the current context and environment. If none is in place, begin the process of establishing one right away, keeping in mind that it’s a journey and not a one-off initiative. If your company lacks internal capacity in this area, or if there’s ambiguity around where to start, a third-party advisor can help concretise the big picture, sharpen focus and define actions. 
2. Set a clear purpose. What is it going to be used for and what business objective can it help attain? Who will benefit from it? Knowing the purpose of the data strategy determines the magnitude, pace and parameters of the implementation.
3. Implement your strategy with the right people by aligning your data strategy with your analytics strategy. Data strategy is an important pillar, but it will not hold by itself. The key to successful implementation is getting the right people on board, such as data scientists, who know how to analyse and interpret the data, draw the right conclusions for it and accurately present the results to the decision-makers and senior leaders.
4. Build a data governance strategy. An end-to-end data-driven journey covers data collection, storage, management, governance, analysis, extracting insight, coming up with actions, implementation, monitoring, and tracking success. Data strategy is the first component where the company decides on all the fundamentals - what data to collect (data types and quantity), what technology infrastructure needs to be created (platform, hardware-software), what skills need to be acquired (data scientists or resident analysts, in-house capabilities or reliance on partners). Data management is also a business of trust and integrity. Good data governance reflects organisational stewardship, ensuring data is accurate, consistent, secure and used ethically. Additionally, clean and quality data enables companies to be more agile and ensures they have the right information in hand to make the best decisions.
5. Continually assess whether the data strategy demonstrates actionable insights. Data is a great storyteller. Ensure that your data strategy yields meaningful insights that inform decision-making and foster innovation; when it stops doing so, it may be time to re-assess and update.

Data might be your most under-utilised asset. A well-crafted data strategy can define the future of asset-rich organisations. Connect with us and learn how GHD Digital can help you harness the potential of data to drive differentiation and make faster and better business decisions.