Data refers to all computer data collected by various means such as, EDI, applications, cookies or IoT connected objects. The security in the transmission of this information makes it reliable to use. Companies that implement a data strategy get more reliable and relevant answers that allow them to improve their performance and user experience, especially as part of a technology project. They know exactly what their customers need – almost in real time – which gives them the opportunity to demonstrate their agility in the immediate adaptation of their offer to demand.
What is a roadmap?
The roadmap is generally defines the ambition of a project as a whole, revealing its long-term milestones. It is designed to deploy a long-term vision and position itself very high upstream of the project, in order to decide judiciously on the course of action and to anticipate all the stages.
The objectives of the roadmap are simple and boil down to checking the adequacy between the actions implemented and the company’s strategy, but also to verify that the managers correctly disseminate the intentions of this strategy. As such, employees’ adherence to the guiding vision is decisive, as the success of the project depends largely on their involvement.
Start by defining the information you need to retrieve and analyse
In the cadre of a data project, defining the information to be retrieved and analysed will be your starting point. You will, depending on the situation of your company, have two possible approaches:
- An approach to the evaluation and identification of existing or future assets. At Devoteam M Cloud, the first step is very often to discuss the customer’s data assets. We carry out a work of identification of the sites to be carried out to make it possible to make the inventory of the heritage of e data within the company, by the evaluation and the identification of the existing data capital or to be created to be able to work.
- A “product/solution” approach that will be either oriented, in the event that you have already chosen a solution, or more open, in the event that you start from an internal problem within the company. At Devoteam M Cloud, these two axes are observed, in the first case, when the customer already has a technological solution and wants to define a roadmap from a very specific technology (e.g. Power BI, Azure Synapse…), and in the second case, when the customer really wants to start from the problem and define, in an environment that is often “very Microsoft”, what is Microsoft’s response and what is the path to reach it.
Thus, a data roadmap makes it possible to define everything that is “data” in the company and therefore based on a data patrimony that is already existing or that will have to be created.
Thanks to the data roadmap, you will be able to define a data strategy by obtaining a big picture target, that is to say an overall vision where we will define the target in terms of solution architecture and the main steps and elements necessary to achieve it (solutions, licenses, organizations, construction sites, resources, training …).
Roadmap data in practice
A data project will bring together all the actions necessary to obtain information and analyse it. A data project will make it possible to bring together the different insights that the company needs.
Any data project must be driven by the business lines that are the starting point of the project. They are the main customers and they must explain their business.
The very principle of the roadmap is to know how to adapt continuously and evolve as the project progresses. The roadmap is made up of living elements, in perpetual motion, it is not fixed. It will adapt according to products, solutions, business challenges, budgets and business priorities that can constantly evolve.
Gathering all the information that results from these changes in the test and learn mode, allows innovative companies to define the data strategy adapted to their market.
Best practices to follow in terms of methodology for your data roadmap
- Carry out ideation/brainstorming workshops with the business to highlight the most interesting data use cases in terms of values for them. The idea was to ignore feasibility and bring out new ways of processing data in an ideal world that could generate value.
Output : Precise description of the use cases and describe for each of them the value generated, the customer satisfaction provided and the level of business priority that can be used as an entry in the final evaluation table.
- Carry out workshops with IT to evaluate the technical feasibility of each of the use cases both in terms of tooling (ETL, BI..) but also in terms of availability and quality of the necessary data (Does my data exist? Where is it stored? And is it of good quality?) and the skills of the customer teams.
Output : Matrix need for future data by use case, technical/realistic feasibility note of the final evaluation table.
- Finalize the study by consolidating all the information in a final deliverable that contains:
- A Synthesis matrix where we will position all use cases according to 2 axes
– General value: Additional income / savings brought & improvement customer satisfaction
– Complexity: Availability/quality of data & available tools & skills
