More than 20 years after the completion of the Guggenheim Museum in Bilbao, modern organisations can learn key data architecture principles from its success.
The Guggenheim Museum Bilbao is one of the most admired works of contemporary architecture and some regard it as the greatest building of our time. It exemplifies the value great architecture creates.
Frank Gehry’s architectural genius transformed the city of Bilbao. Since the building opened it has attracted more than 20 million visitors, directly or indirectly employing 5000 people, and contributed more than $ 3.5 billion to the wider Basque economy.
Within 3 years the resultant tax windfall had more than paid for the initial cost of the building. Perhaps more remarkably the building was even constructed on time and budget.
The architecture was so successful in creating exponential value for its stakeholders that the transformation is dubbed the “Bilbao effect”, with many cities attempting to replicate its success.
Architecture vs Data Architecture
Architecture is both the process and the product of planning, designing and constructing a building. Great architecture is purposeful and contextual, and creates exceptional value for its stakeholders.
Great architects are highly qualified, having the skill to create designs that meet and exceed their stakeholders’ requirements and visions. They have the breadth and depth of knowledge to understand the materials, skills, cost, and feasibility of their designs.
Constructing a building and data landscape are not dissimilar: great data architecture creates value, it requires a great data architect and great architects require four key foundations: strategy, governance, finance, and technology.
There are many examples of businesses creating exponential value from great data architecture. We will explore these in following blog posts.
Unfortunately, many organisations are struggling to create successful data architecture. This failure stems from not enabling data architects through four key foundations:
Data architects need to understand the organisation’s strategy in order to design effective architecture. The strategy enables data architecture (the process), whilst data architecture (the product) enables the strategy. Together they combine to create exponential value.
In 1992 the Guggenheim Foundation had 2 major problems: it could only display 3% of its 6000 artworks and visitor numbers were stagnant.
Thomas Krens therefore developed a strategy to expand the franchise internationally by building satellite institutions around the world. These new institutions would use architecture as the solution to their marketing problem, building a brand whilst creating the space to exhibit more of its collection – a brilliant, simple and differentiated strategy. Krens communicated this strategy to Frank Gehry, and unsurprisingly Gehry got the vision and built on it in the most compelling way.
Unfortunately, the majority of organisations do not have a clearly differentiated strategy. Imagine if Krens’ strategy only revolved around stunning architecture, or solely focussed on international expansion. The beauty of the Guggenheim is that the design strategy combined the two. Without this, Bilbao and the Guggenheim Foundation could well have been constrained to international or architectural mediocrity.
Data architecture created without strategic alignment often results in one of 3 main attitudes: “something is better than nothing”, “let’s copy what our competitors have done”, or most dangerously of all, “let’s buy the best technology, it will solve all our problems”. These attitudes have the ability to destroy massive amounts of value.
In the case of the Guggenheim, many were angry at the massive use of public funds for a “vanity” project where the end value outcome was so distant and intangible.
Many people did not understand how a museum could become an economic motor, instead wanting the investment for the modernisation of their factories. However, the governance policies agreed by Frank Gehry, the Guggenheim Foundation and the Basque Government, so-called “organisation of the artist”, ensured the project was sponsored and executed brilliantly. Great architecture is not just about the design, as Thomas Edison said:
“Vision without execution is hallucination”
Data transcends traditional business units and organisational structures, as a result, data architecture needs to transcend the same boundaries. Inevitably this creates friction, political tension and ownership struggles which often interferes with, and distorts the architecture. This distortion often creates huge costs because the end product doesn’t fit with the strategy and has to be reworked.
Sponsorship is the key to effective governance of data architecture. The architect does not normally have full control of all the resources required to enable the successful and “clean” implementation of a great data model. Many old structures and empires need to be demolished in the process.
The Guggenheim wasn’t cheap, costing approximately € 136m. Yet 20 years on it is clear that it has created enormous value for its stakeholders. This value isn’t only economic, but cultural, aesthetic and environmental.
Data architecture is costly, whilst the value that it creates is extremely hard to measure and monitor. Financing data architecture requires a view of the value potential of data, the risk to this potential, and the initial and continuous costs of the architecture. It requires the intangible value of data to be brought down to the tangible level. (You can read more about intangible value in our previous blog post).
Due to the mathematical complexity of Gehry’s design, he decided to work with an advanced software initially conceived for the aerospace industry, CATIA, to faithfully translate his concept to the structure and to help construction. It was one of the first instances of successful utilisation of Building Information Modelling (BIM) to revolutionise the construction process.
Technology underpins data architecture, but architecture should never be dictated by the technology. The strategy and vision should always be foremost in the mind of the architect.
Look out for Anmut’s future posts which will focus on the interplay between strategy, governance, data architecture and competitive advantage with industry focused case studies.