Digital and Analytics Literacy is a Business Imperative for the 21st Century Organization
This blog is a continuation of the Building AI Leadership Brain Trust Blog Series which targets board directors and CEO’s to accelerate their duty of care to develop stronger skills and competencies in AI in order to ensure their AI programs achieve sustaining results.
In this blog series, I have identified forty skill domains in an AI Leadership Brain Trust Framework to guide board directors and CEO’s to ensure they can develop and accelerate their investments in successful AI initiatives. You can see the full roster of the forty leadership Brain Trust skills in my first blog.
Each of the blogs in this series explores either a group of skills or does a deeper dive into one of the skill areas. I have come to the conclusion that to unlock the last mile of AI value realization that board directors and CEOs must accelerate building a unified brain trust (a unified set of leadership skills that are hardwired in relevant digital and AI skills) to modernize their organizations more rapidly.
Knowledge is key and if you locked up a room of board directors and CEOs in a board room and asked them (1) What steps are required to build a successful AI strategic plan and journey roadmap – what do you think would be the outcome? or (2) Where are your AI Investments and have you inventoried them or audited them? or (3) What is the difference between a computing scientist, a data scientist, and an AI scientist – would their digital literacy skills be sufficient enough to lead and guide their organizations forward? (4) What has been your Return on Investment (ROI) and value realization in your AI programs and/or AI products/solutions?
Sadly, I think we would find some very serious operational execution gaps in realizing the last mile in AI.
A great deal of R&D exploration and AI modelling exploration is underway but moving to sustaining operating practices and ensuring the ongoing knowledge of AI modelling outcomes, and value realization practices remain a major gap in the strategic deployments of AI programs.
In my last blog, I discussed the importance of Data Analytics Literacy as one of the key technical literacy skills in building AI capabilities that are robust and operational focused. This area is so critical that it is a three part series blog, the first blog set the stage on the definition of data analytics literacy, and provided a list of questions relevant for CEOs and Board Directors to ask to advance their Data Analytics Literacy enablements to support a broader strategic foundation for AI Enablements. This second blog discusses the strategic leadership behaviours needed to advance data analytics literacy.
1. Research Methods Literacy
2. Agile Methods Literacy
3. User Centered Design Literacy
4. Data Analytics Literacy
5. Digital Literacy (Cloud, SaaS, Computers, etc.)
6. Mathematics Literacy
7. Statistics Literacy
8. Sciences (Computing Science, Complexity Science, Physics) Literacy
9. Artificial Intelligence (AI) and Machine Learning (ML) Literacy
Data Analytics Literacy (Part Two of Three Blogs)
As a quick recap, According to Gartner Group, data analytics literacy means “ the ability to read, write and communicate data in context, including an understanding of data sources and constructs, analytical methods, and techniques applied – and the ability to describe the use case, application and resulting value.”
What leadership behaviours must a Board Director a CEO exhibit to demonstrate a data analytics mindset?
Earlier in my career, I was fortunate to work at Xerox where business process orientation and fact oriented leadership were critical skills cultivated across the corporate culture and in General Management (GM) roles. General Electric and IBM were very similar to Xerox, in terms of their leadership skill and employee on-boarding programs. These earlier management training programs were all deeply rooted in Edward Deming’s Total Quality Management (TQM) and Business Process Re-engineering (BPM) leadership development programs which embedded data analytics leadership proficiency “fact-gathering” skills. There are a number of key skills, in particular, that supported these strong cultures which ensured data analytics literacy leadership approaches to business problem solving were foundational.
This blog addresses three of the leadership skills:
As discussed in the prior blog, here is no question in my mind that if companies do not super-charge data driven leadership competency development, they will not grow, and will cease to exist as AI enablements are rapidly underpinning all operating processes, as businesses are under massive modernization for survival in an increasingly more intelligent data smart world.
In summary, this blog reinforced the importance of data analytics literacy in terms of three leadership behaviours 1). Recruit the Right Talent 2.) Speak with Authenticity and Candor and 3.) Be Curious and Brave. Board Directors and CEO’s must “ walk the analytics literacy talk” to guide their organizations forward.
Board directors and CEOs need to step up more and ensure that their digital business models that are leveraging AI have strong foundations where data analytics literacy is recognized as a critical skill competency to build trusted AI centers of excellence.
This being said their own leadership and employee engagement practices will determine their odds of success. Like in most transformational areas, the vision must start from the top, and this means – board directors and CEO’s must reflect on their own depth of digital and data analytics literacy and make investments for not only their own relevancy, but also for ensuring they are in fact – leading with analytics confidence.
To see the full AI Brain Trust Framework introduced in the first blog, reference here.
If you have any ideas, please do advise as I welcome your thoughts and perspectives.
Dr. Cindy Gordon is a CEO, a thought leader, author, keynote speaker, board director, and advisor to companies and governments striving to modernize their business