Eliminating organisational silos is a critical aim of digital transformation initiatives, yet many organisations fail to identify the majority of the silos present.

Silos can be categorised into two main types: Visible and Invisible. Visible silos are easily identifiable, encompassing organisational structures, inter-departmental cultures, and geographical locations. These are typically the focus of organisational efforts, despite a lack of deep understanding of the subtler, yet more challenging, invisible silos.

Invisible silos, although not truly invisible, are often overlooked compared to their visible counterparts.

This article explores three key reasons why invisible silos exist around your organisation's data and their implications for digital transformation.

1. Historical Context: Digital transformation often aims to establish data governance and awareness. However, the realisation usually comes late that knowledge of the organisation’s data has been compartmentalised into niche areas. This specialisation means that individuals only consider the data relevant to their specific roles, ignoring its potential value to other parts of the organisation. It’s crucial to acknowledge the pre-existing data silos and implement appropriate governance and frameworks right from the start of any transformation initiative.

2. Organisational Structure: A successful digital transformation will lead to a new operating model that enhances the customer and employee experience. This model, ideally less hierarchical, encourages team autonomy, diversity, and transparency. However, without access to necessary data, this new structure can set the organisation up for failure. Designing an operating model must ensure all relevant data is shared organisation-wide, as appropriate.

3. The Shadow IT Phenomenon: Shadow IT involves the unauthorised procurement and use of IT solutions. It emerges for various reasons but significantly contributes to the invisible data silo issue. Shadow IT solutions become critical data repositories within teams, often without approval or awareness from the IT department. These applications, difficult to discover and integrate into the enterprise landscape, underscore the challenges of managing data across the organisation.

The Path to Success

Achieving collaboration and data sharing is a fundamental outcome of digital transformation.

This requires a comprehensive understanding of available information, its relevance, and governance. Implementing an enterprise data governance framework is essential before starting the transformation process. This framework should include:

1. Data Governance Policies and Standards: Rules and guidelines for data management and usage, including quality standards, security policies, and regulatory compliance.
2. Data Stewardship: Appointed individuals responsible for data quality, security, and governance policy adherence.
3. Data Quality Management: Processes and tools to ensure data accuracy, completeness, and reliability.
4. Data Security and Compliance: Measures to secure data and comply with regulatory requirements.
5. Data Architecture and Integration: Guidelines supporting data consistency and accessibility.
6. Metadata Management: Documentation of data definitions, relationships, and lineage.
7. Change Management: Procedures to manage data and IT system changes effectively.

Ongoing training and awareness are crucial to support the data governance framework, ensuring it remains effective throughout and beyond the digital transformation journey.

The enterprise data governance framework is a living framework that can be updated over time; however, you should never commence your transformation journey without it.

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