Data driven culture, visual management, data aggregation, API, KPI are terms that everyone knows but are difficult to define. This is why we have decided to provide you with these definitions which can be understood by everyone.
Data aggregation allows several pieces of information to be correlated to define (among other things) a key performance indicator (KPI).
API (application programming interface)
Allows two pieces of software to communicate with one another and share information automatically and securely. It can be used to launch processes and exchange data between different tools. It becomes reasonably easy to select data based on the requirements of business teams.
The concept of Big Data became popular from around 2010. It is defined as a bulk set of unrelated data which can be sorted, stored, analysed and distributed.
Business Intelligence (BI)
Aggregation of data to support decision-making reporting. Is about making data intelligible, often using visual dashboards over a certain period and not in real time. BI (Business Intelligence) tools can aggregate large quantities of data, often with intense processing which requires perfect machine configurations and often long development time scales. These dashboards are often more appropriate for managers than for operators.
Is an approach to making strategic decisions based on the analysis and interpretation of data. In other words, examining and organising data to facilitate decision-making with an alignment between company strategy and the objectives of each business area and reinforces the flexibility needed to operate companies effectively.
Also called structured information, this is data organised around themes. Data are always updated in the same way. For example, an email address is structured data because it always takes the same format.
Unstructured data is information where the format is defined in different ways and may or may not contain certain fields. For example, an API may request information on tickets: one with title and description fields whereas for another, only the title field is available.
Data driven company
By definition, all companies are data driven to some extent as they are governed by data. But today, a data driven company is one which exploits data to create value and aims for operational excellence.
Operational excellence can be defined as the effective control and monitoring of processes to achieve given objectives. It is to have an organisation governed by fluid processes: The more fluid the processes the more efficient they are and the better the performance. In a wider sense, operational excellence is about bringing together the key success factors of a company:
- Satisfy the customer by anticipating their requirements,
- For teams to share a common vision,
- Place people at the centre of the process giving priority to trust, team working and training,
- Improve products and services while reducing waste,
- Involve partners in company strategy.
Have a collective performance greater than the sum of individual capacities. Gather around problems to find a solution for many: faster, more efficiently or more efficient. Digital can be a precious help to encourage collective intelligence.
Key Performance Indicator. The KPI is always defined to meet a goal. It comes from a set of information that becomes consistent once aggregated.
Method to visualize KPIs and key information related to the activity of a team: see where the elements are throughout the chain, flow and process. There are several forms of visual management:
- performance Visual management: visual management of KPIs, highlighting of results and display of problems
- activities Visual management of : task management, sharing of information in open space
- project Visual management: visibility of all company projects (steering, monitoring, resources, etc.)
- flows Visual management : visualization of the value chain, lead-time analysis, management of logistics flows, etc.
Obviously, this list is not exhaustive but allows you to better understand these different terms and to be able to communicate them to your teams to support them in your data-driven culture process.