Maximizing Value: Achieving More in Less Time
Written on
The Essential Frameworks for Data-Driven Success
Welcome to your weekly digest focused on Data, AI, and Analytics. This blog serves as your go-to source for the most trending stories in the data sphere, filtering out what's essential and what isn't. If you're pressed for time, feel free to WATCH the Weekly Vlog here. Prefer listening? You can also tune into the Weekly Podcast here.
Additionally, there's a special treat for you at the end of this post: a well-organized slide deck filled with valuable resources and links. Don’t hesitate to scroll down and grab it for FREE to share with your network.
Now, let’s dive into the top five stories in Data, AI, and Analytics for the week!
- Doubling Value in Half the Time Through Digital Platforms
According to the Boston Consulting Group, organizations can achieve double the value in half the time and costs by implementing a Data Digital Platform (DDP). The foundational elements of a DDP include:
- Isolating data from core transactional systems such as ERP and CRM.
- Developing modular interfaces between systems using APIs.
- Utilizing Cloud infrastructure for enhanced speed and agility.
- Creating a digital interface that adjusts to the needs of customers, suppliers, and employees.
- Harnessing AI and open-source software.
- Integrating both internal and external data sources.
- Offering data as a service to an omnichannel smart business layer that provides value every few weeks, rather than the traditional 12 to 18 months.
To excel in this area, leaders must address five fundamental questions:
- What are the leading examples of digital success across various sectors today?
- How does our organization measure up against these top-tier examples?
- Is our ambition clearly defined in comparison to industry leaders?
- If our current digital projects were completed today, how close would we be to best-in-class?
- What is the realistic timeline for completing these digital initiatives?
For more insights, click here.
- Eight Essential Habits of Successful Data Scientists
Harsh Gupta identifies key habits that contribute to the success of data scientists, including:
- Focused Reading & Continuous Learning
- Listening for Business Challenges
- The Importance of Saying No Often
Do you agree? Share your thoughts and let him know what additional habits could be included. Perhaps we can expand this list to ten!
- Understanding the Distinction Between Data Science and Business Intelligence
Stan Pugsley offers valuable insights on this topic. What are your thoughts? Connect with him here.
- Should Analytics Teams Be Centralized Under a Chief Data Officer?
Mike Rollings advocates for this structure. What do you think?
- The Importance of Reference Architectures
Approximately 70% of financial institutions surveyed have maintained a modern data-architecture roadmap for 18 to 24 months, yet nearly half still operate with disparate data models. Most have integrated less than 25% of their critical data into the target architecture. McKinsey provides strategies for reducing costs in traditional AI applications while enabling quicker market entry and improved reusability for new AI projects.
I truly appreciate the value of well-tested architectural frameworks!
I hope you found this information beneficial. Please leave a comment and a like if you did. Interested in connecting? Find me on LinkedIn @ linkedin.com/in/brunoaziza
Chapter 2: Video Insights
This first video explores strategies to increase productivity, emphasizing the importance of effective time management and structured workflows.
The second video features Jeff Sutherland discussing how to optimize processes and achieve greater results in a shorter timeframe, utilizing Scrum methodologies.