Transforming Data and Analytics Delivery Management: The Rise of Platform-Based Delivery

Artificial Intelligence (AI) has already started to transform the way businesses make decisions which is placing ‘n microscope on data as the life blood of AI engines. This emphasises the importance of efficient data management pushing delivery and data professionals to a pivotal challenge – the need to enhance the efficiency and predictability of delivering intricate and tailored data-driven insights. Similar to the UK Government’s call for transformation in the construction sector, there’s a parallel movement within the data and analytics domain suggesting that product platform-based delivery could be the catalyst for radical improvements.

Visionary firms in the data and analytics sector are strategically investing in product platforms to provide cost-effective and configurable data solutions. This innovative approach involves leveraging standardised core components, much like the foundational algorithms or data structures, and allowing platform customisation through the configuration of a variety of modular data processing elements. This strategy empowers the creation of a cohesive set of components with established data supply chains, offering flexibility in designing a wide array of data-driven solutions.

The adoption of product platform-based delivery in the data and analytics discipline, is reshaping the role of delivery (project and product) managers in several profound ways:

  1. Pre-Integrated Data Solutions and Established Supply Chains:
    In an environment where multiple firms develop proprietary data platforms, the traditional hurdles of integrating diverse data sources are already overcome, and supply chains are well-established. This significantly mitigates many key risks upfront. Consequently, product managers transition into roles focused on guiding clients in selecting the most suitable data platform, each with its own dedicated delivery managers. The focus shifts from integrating disparate data sources to choosing between pre-integrated data solutions.
  2. Data Technological Fluency:
    To assist clients in selecting the right platform, project professionals must cultivate a deep understanding of each firm’s data platform approach, technologies, and delivery mechanisms. This heightened engagement with data technology represents a shift for project managers accustomed to more traditional planning approaches. Adapting to this change becomes essential to provide informed guidance in a rapidly evolving data and analytics landscape.
  3. Advisory Role in Data Platform Selection:
    As product platform delivery gains traction, the demand for advice on data platform selection is on the rise. To be a player in the market, data solution providers should be offering business solutions aimed at helping clients define and deliver data-driven insights using product platforms. Delivery managers who resist embracing this advisory role risk falling behind in the competitive data and analytics market.

The future of data and analytics seems poised for a significant shift from project-based to product-focused. This transition demands that project professionals adapt to the changing landscape by developing the capabilities and knowledge necessary to thrive in this new and competitive environment.

In conclusion, the adoption of platform-based delivery for complex data solutions is not just a trend but a fundamental change that is reshaping the role of delivery management. Technology delivery professionals must proactively engage with this evolution, embracing the advisory role, and staying abreast of technological advancements to ensure their continued success in the dynamic data and analytics industry.

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