Being Agile in Analytics
Speed to market is crucial for staying ahead of the competition when developing products or services. As an executive decision maker, having timely and directionally correct intelligence often outweighs perfect data that arrives too late. This need for speed is paramount in both BI and AI domains.
So, how does one achieve speed?Our recommended combination is AGILE DEVELOPMENT + ARCHITECTURE. Agile development enables short-term speed, while architecture determines speed in the medium and long term. These two disciplines are not contradictory; solutions can be designed to leverage both. However, sometimes tensions or tradeoffs arise between short-term and long-term goals, making it vital to implement a development process that balances both concerns with wisdom and experience.
Two common flavors of agile are available: SCRUM and KANBAN. The choice depends on the specific project and context. Nevertheless, the key lies in understanding the underlying principles and adhering to them. Merely hiring a scrum master, setting meeting cadences, implementing CI/CD, and following practices are not foundational principles; they are ways to apply the principles.
I particularly appreciate Marty Cagan’s description of Agile:
- Tackling risks upfront
- Collaboratively defining and designing the “product”
- Focusing on solving problems rather than just implementing features
In the coming weeks and months, we will delve deeper into how to effectively use agile and master other disciplines like architecture. Stay tuned for more insights.