Understanding the Imperative of Data Strategy

To succeed in a dynamic environment, both businesses and nonprofits should strive to make the most out of data; this is where a data strategy comes into play ... 

In a volatile, uncertain, complex, and ambiguous environment, organizations need to constantly adapt and evolve. This is especially true for fundraising nonprofits, as their sector is increasingly embracing digital transformation. This transformation isn't just about adopting new technologies but reshaping how organizations operate and create value as well as impact for their stakeholders. Digital transformation can be a driving force that propels organizations into the future, enabling them to be more agile, customer-centric, and efficient. To a significant extent, the history of digital transformation was coined by the evoluation of data and its use.

The Evolution of Data 

From the 1950s to the 2000s, businesses relied mainly on descriptive analyses. Reports gave an ex-post view on processes and their results. These were relative „simple“ times, with a focus on internal, structured data from databases and spreadsheets. Around the turn of the century, there was a shift. The 2000s saw the rise of digital data. Innovative, data-driven business models began to emerge. Although there was an ongoing focus on descriptive analyses, the scope widened to include unstructured and external data, for instance from the web and social media platforms.

Fast forward to today, and we are witnessing another paradigm shift. Organizations, both from traditional industries and those built on digital business models, are leveraging data-driven decision-making. Predictive and prescriptive analyses aren't just buzzwords but becoming imperatives. It is clear that both structured and unstructured data hold equal relevance, positioning analytics as a core function in any organization.

Data is a pivotal resource in Digital Transformation and the sheer volume of data generated today is mind-boggling. However, data essentially is not more than a „raw material“ like oil or wood which need to be cleaned,refined, processed etc. Using data the right data in the right way for the right purposes can be an key success factor for modern organizations. This is where data strategies come into play.

Dimensions of a Data Strategy

Navigating an ocean of data requires a compass, a robust data strategy. A data strategy can be defined as a comprehensive plan to identify, store, integrate, provision, and govern data within an organization. While a data strategy is often perceived as primarily an “IT exercise”, a modern data strategy should encompass people, processes, and technology, reflecting the interrelated nature of these components in data management. A data strategy is not an end in itself. Ideally, it should align with the overarching strategy of the organization, as well as the fundraising and IT strategies. A closely interlinked area with a data strategy is the analytics strategy. It's crucial to ensure synergy between these strategies for the successful exploitation of data insights and value creation.At least six dimensions of a data strategy can be named.

• Identify: A data strategy should ensure all data can be effectively identified, treating data as a vital corporate asset.
• Store: Current methods in IT organizations efficiently manage storage for individual application, be in the cloud, on premise or within hybrid approaches. These methods should cater to various needs in organizations such as transactional processing, analytics, and general-purpose data storage for various file types.
• Integrate: Data integration should aim to consistently and reproducibly distill and combine data into coherent datasets for further use.
• Provision: Data provisioning is the process of making data available in a structured and usable format to users, applications, or systems that need it. It involves collecting, preparing, and distributing data.
• Govern: Data governance is a comprehensive set of policies and rules that apply to all applications, systems, and staff, ensuring consistent data management. Its aim is not to limit data access, but to facilitate its usage and sharing. An effective data strategy must include integrated data governance to handle changes in technology, processing, and methodologies.​​

​Crafting a Data Strategy

In a nutshell, the crafting of a data stragey can be achieved following four generic steps.

1. Define business objectives that are relevant to your data strategy by involving relevant stakeholders from across your organization´s functions. Alignment with the overall business strategy, fundraising strategy and IT strategy should be considered.
2. Indentify the range of your (potential) data sources and figure out where and for what purpose you have data that may be relevant, considering your objectives.
3. Indenfiy data uses cases by thinking big and starting small. Rank these uses based based on criteria that are suitable for your context.
4. Draft a roadmap that outlines initiatives related to technology, processes, skills, and culture

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​Four Commandments for your Data Strategy

One should consider at least four recommendations when starting to develop a data strategy.

1. Create clear data-driven use cases based on realistic goals, clear success criteria and stakeholder involement
2. Derive your data requirements from the uses cases and fill gaps in the availabilty of relevant data.
3. Choose the right technology to support you but and be aware that there is no „silver bullet.Get governance right and find a balance taht fits your organizations and objectives
4. Consider the people dimension, i.e. define the capabilities you need and invest in education and inspiration of your teams.

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So what?

According to experts like Bernard Marr, an influential author, speaker, futurist and consultant, organizations that view data as a strategic asset are the ones that will survive and thrive. It does not matter how much data you have, it is whether you use it value-creating and impact-generating way. Without a data strategy, it will be unlikely to get the most out of an organization´s data resources. In case you need a sparring partner or somebody to accompany you on your data strategy journey, please do not hestiate to get in touch with us.
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All the best and have a great third quarter!
Johannes