Development of Data Strategy for leading global provider of professional assurance services

Our client is a leading global provider of professional assurance services that help businesses manage risk, improve sustainability and achieve their goals. With a globally known brand name, it is a trusted partner to a diverse range of clients worldwide. 

Our client operates in a wide range of industries, including aerospace, automotive, food and beverage, healthcare, and more. Their services include certification, training, assessment, and verification, which are designed to help organisations operate more efficiently and effectively. 

With a global network of employees and contingent workers, our client has a wealth of expertise and knowledge to help their clients achieve their goals.  

Challenge

Following completion of a large separation and becoming an independent business, and a series of ambitious acquisitions, it had become apparent that our client did not have a single cohesive approach to data management, governance and monetisation.  

There were a growing number of risks & issues, and as a data strategy had not been fully developed, socialised, or executed against, there existed misalignment at all levels within IT and the wider organisation. Further drivers for a joined-up data approach included the strategic ambition to further monetise the data assets held by them to open up additional revenue streams. 

To address this challenge, and bring much needed clarity and focus, we worked to develop the company’s first data strategy, through working with business and IT stakeholders across the various business lines, whilst also providing ad hoc advice on the data operating model. 

Solution

Our approach involved a rapid and in-depth discovery phase (4 weeks) whereby we took insight from the business and IT leaders within the organisation. Throughout our discovery and strategy development we considered a wide range of data lifecycle principles including; Master Data Management, Governance, Policy and Processes, Quality, Data Warehousing, Reporting & MI, Integration, Architecture, Modelling and Design.  

Importantly in consideration of the core data principles we understood what was important to our client as a business, by hearing what key stakeholders had to say and understanding the values and strategic direction of the organisation. The Data Strategy was then developed and socialised in an iterative fashion with our key stakeholders to ensure alignment as to the direction of the recommendations.  

Our output at a high level, included:

• A current state assessment of the ‘as is’ data landscape that allowed us to identify key areas of ‘The Data Value Chain’ that required focus by the organisation to achieve their strategic objectives 
• A target state view and corresponding roadmap, detailing x7 key initiatives/workstreams recommended in order to achieve data alignment across the organisation and therefore mitigate the security threats posed and also to progress the strategic ambition of further monetisation of data 
• Recommendations at a more granular level in order for our client to be able to progress with implementation of the strategy 

In addition to the core strategy further direction was provided to detail the governance mechanisms (including forums and processes) required to embed a culture of data ownership and stewardship throughout the company and a Data Asset Catalogue which provided the client with a first-pass view of what data assets were held and where they were stored.

Outcome

The Data Strategy clearly identified the organisations data needs and provided a concise framework with tangible actions to take forward. Furthermore, it catered to our client’s requirements of providing the comprehensive roadmap and direction it needed to mobilise clear streams of work to build accuracy and consistency into their data through improved governance, management and integration techniques. With these principles in mind, the strategy provided the framework needed for the company to progress with the strategic ambition of leveraging existing data held across the organisation to make informed data-driven decisions and achieve business objectives, such as the wider monetisation of data assets. 

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