With over 16 years of implementing data solutions for our customers, across a wide range of technologies, industries and functions, Insight Consulting’s strategy division has developed and honed a framework for implementing successful data strategies which maximise our customer’s ROI on their data investments.
Our Data Strategy framework is the underlying fabric of the data value chain, providing a structure to partner with our customers to define and implement data strategies, upskill knowledge workers through data literacy programmes, and create a long-lasting data culture, ultimately ensuring optimal ROI on data investments and assets.
Whilst the framework provides a structure for our customers’ data journey, each customer is unique, and our data strategists partner with our customers to advise on and tailor the elements within the framework to each individual customer.
This is why we also refer to our Data Strategy framework as our Customer Journey framework – it encompasses all the elements required to ensure our customers’ successful navigation through their data journey, no matter where they are on the data maturity scale.
There are four main elements to a data strategy within an organization
Creating a data vision is the first step towards leveraging more of your biggest asset: Data.
The process of creating a data vision involves engaging with key stakeholders to identify, understand and clearly define the business objectives and opportunities. Our data strategists then work with the stakeholders to translate these business objectives into data driven KPIs and measurements. The data objectives should always support the business priorities; as a result, the data vision should be revisited over time to ensure that the business strategy and the data strategy remain clearly aligned and symbiotic.
Once the gaps have been understood, the next step is to create a recommendation for the technology architecture required to close the gap between the As-Is and the Future state of the customer’s information universe. The architecture definition is product and platform agnostic – describing the requirements for the necessary technology in detail. It is in essence, a document that can be used to evaluate various technologies and vendors, including existing investments, against a set of criteria required to achieve the desired endstate.
Choosing, categorizing and prioritizing data projects is key to the successful implementation of a data strategy. Long term data projects need to be balanced with a parallel stream of quick wins in order to ensure user buy-in, and maintain the momentum of the data strategy implementation. Resource plans (people and technical) need to be considered here, and curating the right data projects is a careful balancing act which requires buy-in from top level stakeholders in the organization.
Data only becomes valuable to an organization when it is used to create action directed at improving performance, meaning that a fundamental principle of successful data strategies is the ability of business data users to understand and analyze the data with the objective of creating growth – in other words, the establishment and maintenance of a robust data culture in the organization.
The creation of a data culture is an ongoing process, and whilst each organisation is unique, there are several underlying common threads that will ensure the success of their efforts in building and maintaining a long-lasting data culture, one of the fundamental cornerstones being the data literacy of the workforce.
Data literacy is the ability to read, write and communicate data in context. Insight Consulting has developed business oriented Data Literacy courses, aimed at upskilling knowledge workers at all levels of the organisation. We understand that there is no one size fits all approach – not everyone needs to have the same level of data literacy. Our courses are therefore targeted at users with different needs, skills and aspirations, ensuring that everyone is empowered to use the data available to them to maximum benefit.