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The IMI’s aim was clear, collaborate with a highly consultative IT partner to take the business forward from a financial reporting perspective. Initially chosen for a Sage 200 support role, a later requirement on analytics – specifically the implementation, visualisation, and surfacing of Sage 200 insights through Power BI – led to BCN working on the complex visualisation project of the IMI’s management accounts.
Founded in 1920, the Institute of Motor Industry today supports more than 85,000 professionals within the automotive industry, giving voice to a growing membership while delivering accredited training to more than half a million people. Based in Hertford, the IMI has more than 100 employees and an annual turnover of £10m.
Microsoft’s Power BI integrates seamlessly with Sage 200 to give finance teams a quick and easy visualisation of accounts. By consolidating complex data from various sources across the business, and using repeatable processes that ensure data security and compliance as standard, BCN’s Power BI solution gives users a customised and instantaneous picture of accounts, freeing up staff to drive business initiatives.
The Institute of Motor Industry needed to simplify its financial reporting, with the strategic aim of consolidating data to create a single, easy-to-view source for analytics and data-driven decision-making. As part of the project, BCN tackled specific data-mining issues and design features to enhance the efficacy of the solution and the overall user experience.
The discovery phase was instrumental to the success of this project, ensuring not only clear and consistent communication throughout but giving BCN a deep understanding of the issues, needs, preferences and risks. We took a data-first approach, taking time to figure out which data was required, where it was being pulled from and how it worked. This enabled us to build a strategy that not only used the most relevant data, but ensured it was processed and manipulated in a safe and compliant manner before presenting it in a standardised and more meaningful way.
Testimonial
The IMI’s finance team had previously relied on repetitive and time-consuming manual data processes for financial reporting. BCN’s Power BI solution has transformed the way the team works, automating these processes and freeing them up to carry out more interesting tasks that add value to the business.
By simplifying the technology, and making it an enabler of internal business operations, the IMI has been able to streamline and evolve other processes related to customer and sales reporting, as well as for marketing purposes. All the data they need is right there, instantly accessible and easy to interpret.
One of the key benefits of BCN’s solution has been in allowing The IMI to talk less about the technology and more about what they want to achieve as a business. BCN’s Power BI and Sage 200 integration has removed the burden around financial reporting to allow time and space for data-driven innovation and business-focussed evolution. Working with BCN as a trusted technology partner, The IMI has its eyes firmly on the future.
This project has laid the foundations for The IMI’s digital transformation journey, and BCN is already looking at ways of using the same data-driven methodology in other areas of the business. Working together, BCN and The IMI aim to incrementally consolidate data across the business, creating a single source for analytics and data-driven insights that will transform decision-making and bring countless benefits to a growing membership.
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Connecting multiple data sources and transforming the way their performance data is collected, presented, disseminated, and analysed, BCN harnessed Power BI to link the Trust’s data sources and create near real-time data visualisations for 250,000 outpatient appointments.
East London NHS Foundation Trust (ELFT) is renowned across the UK’s public health sector as a pioneer of continuous quality improvement. ELFT now uses SPC Charts to provide its teams with intelligent insights in near real-time to support the prediction of future trends, the identification of variations and data-informed decision-making.
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