.png){kind=logo}
The Analytics Hall of Fame (AHOF) is a merit-based award and recognition site for data analytics and digital professionals who demonstrate significant and publicly verifiable achievements. As a long-time evangelist of data analytics (DA) based business decisions, Anthony Branda, Founder and CEO of AHOF, established the company to develop a practitioner community in this space. The company releases articles with leading-edge content from practitioners in the field and develops gaming functionality to help professionals sharpen their DA skills, share a community experience and have fun!
Founded at Pace University in New York, AHOF conducted its inaugural award ceremony in 2019, honoring famous leaders like V. Kumar, Tom Davenport Vishal Kumar, Randy Bean, and Beth Comstock to name a few.
Anthony has had an enduring 25+ years of career in data analytics, data science, and CRM. Starting his profession as an SQL programmer in database marketing at American Express, Anthony's career began to skyrocket and made him land prestigious roles from being the VP of Cross Sell Analytics at Wells Fargo to leading some of the first analytics and data science units in the industry even before the position of Chief Data or Chief Analytics Officer was known. Besides this, he has led teams at Bank of America, RBS America/Citizens as its CAO, and at Citi, he was leading their North American Consumer and Commercial Decision Management. Recently, he has been applying his skills, knowledge, and experience to analytics and digital transformations in the global arena like the CDAO at ASB – a subsidiary of CommBank, (#1 international bank in Australia), and as the Group Head of Data Analytics for over seven countries in the Gulf Region for Ahli United Bank.
Anthony's claim to fame is demonstrated by his ability to connect the dots and mesh business strategies, technical know-how, and data science into a cohesive approach, communicating and driving consensus with stakeholders to drive the best business and customer outcomes. He has had rotations in all aspects of Banking Information Management and Analytics including consumer, commercial, investments, private and retail banking, and real estate. Anthony claims that he is a vociferous learner, completing Certifications in Analytics (CAP) and Data Science (John Hopkins), and AI (MIT), in addition to earning a Doctorate in Marketing Analytics.
As an evangelist of DA, Anthony founded an M.S. in Marketing Analytics at Pace University. He led a group of experts and industry executives to establish the Analytics Hall of Fame (AHOF), where he is the CEO. Besides, he is also an infamous author in practitioner-oriented journals with articles on how firms can integrate analytics with marketing practices to improve business results.
At the beginning of Anthony's career, he reveals that he learned the criticality of fact-based decisions, and just as importantly, the reality that not all relevant facts are easily and quickly available. Direct marketing enabled him to understand the test and learn concepts and data science methodologies, forming the foundation of his knowledge about measuring success. In the early years of credit cards, Amex, MBNA and Bank of America were formative in terms of extending Anthony's knowledge about statistical methods, omnichannel engagement, and CRM.
As he began leading larger teams, Anthony learned that empathy, clear communication, and fostering change were critical leadership competencies that were important to persuade clients to invest more in analytics and take calculated risks in new test ideas and opportunities. Also, transforming startup functions at CommBank, AUB, and Embrace Home Loans has taught him never to neglect business problem framing and use case identification, regardless of today's advanced technologies.
Rotations at Accenture and running a consulting business gave Anthony an appreciation for the data lakes, cloud-based tech, and open-source tools and how to ensure alignment with solutions for business problems. Like many human endeavors, the use of DA is a marriage of art and science, which would include math, engineering, and tech, which must be appropriately married to the business problem frame. The art stems from deploying the solutions correctly, this is why data analytics and AI are a blend of heavy sciences but also require a fair amount of skill and communication to ensure a successful path to deploy. Anthony is also quite amused by the act of balancing all these variables to drive toward the desired outcome.
Anthony reveals that in his career, he has often run into walls deploying analytics, primarily due to incorrect incentive structures and KPIs, which disincentive analytics usage with relevant customers. For a marketing program, the team generally targets profitable or as many customers as possible or the highest volume of customers. Those are very different objectives with very different program profits and expense results, and customer outcomes. The clarity in articulating the business problem and the desired outcome should guide KPIs with the support of leadership and stakeholders.
According to Anthony, leadership and top management support have been vital to changes in KPIs and removing barriers to success, hence ensuring the accompaniment of stakeholders and maximum management support before building analytics solutions are of primary importance to Anthony. It provides a path to deploy. He takes us through another example of when each LOB has distinct product sale goals for their business. The firm still aims to attract the right customers in the right channel to maximize customer value. The business models and KPIs must be modified through influence and proof points to gain acceptance of this enterprise view. Very often, silos, and even in some cases, agile-at-scale with its tribe mode can create a tribal mentality, which is at the expense of the customer and the enterprise.
Lastly, Anthony claims that data analytics is about prioritization and efficiency gains, whereas business is about volume and scale. Using targeting tools and data science often requires a trade-off between losing volume and hitting the correct targets.
Anthony states that technology is an 'enabler'. Therefore, the businesses that receive the benefits of technology need to be heard. He continues that leadership attributes to facilitate this goal include empathy, listening skills, collaboration, and negotiation. Leaders are SMEs but also diplomats and deal makers- they must work toward compromise as not all technology gets deployed without challenges. Most importantly, technologists must be trust builders and have the willingness to educate others.
Anthony claims that the team deploys a data monetization process to ensure that there is always a pipeline of proactive pilots in the works. When combined with an agile team comprised of data science, test and learn, design thinking, creatives, analysts, and prototyping skills, new initiatives and innovations are developed to grow value, but in a measured and controlled way. This is where lean startup thinking combined with advanced experimentation techniques and design thinking can help the firm get traction with the right solution to monetize for the right audience.
Furthermore, data analytics innovation must be in every organization's budget – bandwidth and resources must be dedicated to remaining competitive in today's world, mentions Anthony. He further adds by exemplifying that an organization might commit the funding for the team to pilot 2 or 3 new test ideas per quarter for subsequent rollout. Beyond BAU insights and analytics, which tend to be more reactive, these pilots, with a defined business case and a definition of success are key to continued growth and value addition.
Anthony remarks that modern leaders must be well versed in cognitive technologies such as deep learning and machine learning, specifically for marketing, customer management, and risk applications. While broad-scale AI adoption is still far off in banking, beachheads are emerging.
In banking, many aspects of AI, automation, and cloud are taking hold, but Anthony believes there is still a long way to go.
He also mentions tools such as Pega and robotic process automation, which make data movement easier, and are essential for CDAOs to understand and deploy. The concept of a single source of truth can be further advanced if we don't have to move data around but using these virtual architectures to access data will be quite a change from current ways of working.
The vision of AI is to have data analytics and Auto ML be the brain behind all decisions in the organization, opines Anthony. That is the focus area for many CDAOs. He continues that changing marketing automation and customer engagement tools into real-time customer decision engines and platforms that drive the next best experience or Next Best Everything will allow the whole vision and uplift to be achieved by using machine learning and other cognitive tech. These tools use recommendation or decision engines to serve the proper interaction, offer service experience, and make risk or underwriting decisions to maximize customer value and drive a good customer experience. The customer data platform and the customer decision engines leverage data Robot, Pega, Adobe, and Salesforce software, as well as the brain trust of data scientists and engineers to make it a reality.
According to Anthony, the idea that investment advisors and bankers can use while scenario planning is to give good guidance and advice using AI to transform banking, and the technique is already making gains but is facing headwinds due to investments in skills and technologies and understanding of the benefits. Other applications such as chatbots and sentiment analytics using NLP or ML have become more mature and continue to be refined and deployed.
For banking analytics, Anthony envisions the role of the CDAO continuing to evolve with more and more companies bringing both the data and analytics together under one roof or leadership to get more traction and ensure that data drives insights that lead to business impacts. The industry has pivoted heavily to engineering and towards a very fractured ecosystem with many technologies and tools. But he believes that companies will swing back to a more strategic and integrated business view over time as the technologies' resource capabilities need to solve a defined business purpose. He adds that in some firms, the CDAO will ultimately report to the COO or CEO, as a peer to the CMO, Digital Officer, CTO, CIO, and CFO. This will happen as data analytics continue to drive impact and be viewed as a business asset to improve all decision-making.
Meanwhile, in terms of the Analytics Hall of Fame, Anthony confirms that the company is pivoting to enable the best content to be shared by practitioners to demonstrate their knowledge and skills. He accredits that there should be a place for data analytics professionals to have their own space to show their know-how outside of business research and the business media reporting on the DA practice as observers. The company aims to carve out a space for data analytics practitioners to describe what they are doing, in their own words and describe their success stories.
When it comes to leadership, Anthony says that leaders and executives generally believe they have developed their role better off than the way they found it. This is a good mindset to have and can often mean the difference between having a job and having a career. But adding the totality of possibilities to one's role makes it more exciting and valuable for the team and firm. "Be curious, listen well, be humble and show empathy to your stakeholders. Learn the latest techniques and practices to transform your business and yourself," he advises. He finishes his statement by asking emerging leaders to make personal transformation as crucial as business transformation.
Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp
_____________
Disclaimer: Analytics Insight does not provide financial advice or guidance. Also note that the cryptocurrencies mentioned/listed on the website could potentially be scams, i.e. designed to induce you to invest financial resources that may be lost forever and not be recoverable once investments are made. You are responsible for conducting your own research (DYOR) before making any investments. Read more here.
