The divide between IT and business is evidently a systemic challenge for most companies. Despite the elevation of functions like CIOs’ or CDOs’, technology leadership is still struggling to collaborate with business and the conflictual IT-business relationship is rooted in the fact that the tech side and the business people are unable to bridge their expertise and skills gaps to work in tandem for the greater success of the organisation.
Yet, in today’s market context, IT-business alignment is inevitable and the lynchpin is recognizing that when IT and business work together, as one, both will achieve more.
As an illustration of the above, I recall a use case with an insurance company that aimed at enhancing the usability and time-to-insight of its data. The CIO decided to launch a data rationalisation program under the data value management program. Doing so, the CIO office did not involve any business stakeholder. The focus of the business cases was centered around cost reduction and rationalisation: decommissioning of data warehouses (servers, licenses), offloading of operational systems. As a matter of fact, the changes were mainly technical and did not involve creating new capabilities nor showing support to the business strategy.
Results, lessons learned and what we can do to help
The business department did not manage to implement the intended roadmap within the CIO office’s data infrastructure. When they finally began to develop the software to support the roadmap, they did it with complete disregard for the existing data infrastructure and thus, spent significant additional resources.
Moreover, as the data initiative was essentially about cost reduction, they did not anticipate mid-term business needs and only rationalized existing capabilities, like BI and reporting. As a result, the CIO office’s project was a total failure because it prioritised cost reduction above business needs.
What we recommend:
- Always onboard business lines and stick to the business strategy
- The data program can show cost reduction, yet creating value is a must
- Having a roadmap of business cases allows us to study the technical requirements that underlie the business’ ambitions. Those technical requirements will help design the ad-hoc data platform that will support the business cases and implement those requirements step by step.
Our data engineering platform, Digazu, is the right vector to successful data projects, connecting business ambitions to technical requirements.
Digazu helps you optimise your data project lifecycle. As a turn-key and low-code data platform, Digazu helps with the orchestration and automation of the data project stages. From the collection, storage, transformation to the distribution (full streaming) of their data, companies were able to act faster and better. The data assets were assembled back properly and distributed to the tools (reporting, data crunching, new apps) made available to data consumers in a standardized and fully managed way.
Digazu helps :
- Accelerating the implementation and integration of a ready-to-use platform.
- Being productive from day one: installed on day 1 and exploiting new datasets in production on day 2.
- Offering control and visibility on your data (wherever they are) by setting up a ready-to-use reference data-centric architecture and connecting all your data sources.
- Improving the work environment agility with full-on scalability and enhanced compliance.
- Working in a user-friendly, customisable and agile environment to manage your data assets in full transparency and efficiency.
- Accelerate the POC to PROD transition, with a reduced time-to-market of their data projects, from “data” to usable “data assets”.