Apex talks to Phanii Pydimarri, Senior Director of AI & Advanced Analytics at Stanley Black & Decker. Phanii is Global Data Analytics Leader with over 15 years of experience in end-to-end Data Management. Today Phanii discusses key elements in the evolving role of the CDO and strategies for fueling cross-functional business growth.
Q: What is the difference between a Chief Data Officer and a Chief Analytics Officer? Are they one in the same?
- To be frank, the definitions on these titles are still evolving. Organizations are figuring out the difference, their area of focus and apparently calling their Data Leader with one of these titles or even better combining them and calling the roles as Chief Data & Analytics Officers
- The major difference I see between them is the Chief Analytics Officers must be more Customer/Business focused. Their main goal should be to understand and identify opportunities to build Analytics products and solutions using the Data managed and enabled by the Chief Data Officer. The Chief Analytics Officer to me is much of a Product Owner, operating like one, designing new data analytics related products that could be both internal and external facing. The eventual goal should can be to monetize the analytics products and provide a revenue source for the organization
- Chief Data Officers on the other end must be able to focus on identifying potential new data sources to tap into, build the corresponding modern data platform and provide high quality, highly governed and compliant data to the analytics teams across the organization. Chief Data Officers can also look for ways to monetize the data by working with both internal and external partners
- Both these roles are evolving and at the present they can be operated by one individual but cannot be called as the same as they both have different areas of focus
Q: How have you seen the role of CDO change? How do you partner with the CIO? Have you encountered any challenges facing the CDO function?
- The role of the CDO has been evolving towards maturity for some time now. Organizations are understanding the role better and identifying critical success factors of the role and eventually bringing it into the corporate leadership mix
- A major welcome change that I would like to call out here is more and more organizations are creating the CDO role and giving the organizational-wide responsibility of managing Data assets to it which shows the gain in prominence the role has gotten over the last few years
- Partnerships across the C-level is critical for CDOs to be successful. A CDO must be viewed as the common thread between the Technical and Business functions within an organization. CDO has the crucial responsibility of collaborating through CIOs and CTOs along with other business side C-level executives.
- Having a great relationship with CIO is important as CDOs may still rely on traditional IT to provide infrastructure and technology support which is crucial for the success of the Data & Analytics initiatives. About 35% of CDOs continue to report into the CIOs which assumes the partnership
- Lack of cross-functional collaboration and inter-functional siloes are major challenges for a CDO
Q: What is the current state of Big Data and AI investment and do you sense the pace of Big Data and AI investment changing?
- There has been a significant increase in corporate spend on Big Data and AI. Organizations are realizing the fact that not recognizing data as the most valuable asset is affecting their competitive advantage and are losing out on potential business opportunities
- I can say that there is significant improvement in realizing value of and from big data by organizations
- On the other hand, investments in AI are just getting started. There needs to be a lot of value-driven measurement that needs to be done by the organizations to really understand if AI can add value to their business model. There are organizations jumping onto the AI bandwagon without doing the due diligence of understanding the ROI and have lost significant investment for nothing
- I expect organizations to improve their investment into AI, Big Data and RPA in the coming days, but would recommend operating with caution by understanding the true value proposition from the investment
Q: What advice would you give an early stage CDO joining an enterprise organization?
- Spend a lot of time understanding the current state
- Identify where the organization falls on the maturity scale
- Plan to move up the maturity scale with small achievable goals
- You do not always need AI, do your due diligence to understand ROI
- You do not always need modern data infrastructure to meet the organizational needs
- Communicate, Communicate, Communicate
Q: How do you balance the need to ensure that non-revenue generating data-driven transformation efforts receive the commitment and funding that are required to sustain these efforts?
- Finding the right balance is the most important task of the CDO. It is highly critical to break down the between Business (Product, Marketing, Sales etc.) and Operational (Manufacturing, Supply Chain, Customer Support etc.) functions. An organization needs equal investments in both areas to see success from being data driven. Organizations tend to ignore operational focus areas as they are not direct revenue generators, but the CDO must take the responsibility of educating the executives, Senior and mid-level management the importance of this.
- A best example I can think of is organizations investing millions of dollars in creating newer products and offerings to their customers but doing minimum to the complaints they receive on their call center lines, social media, or other forums. Organizations can lose out on the sales of their innovative products with bad customer support
- As a CDO it is important to focus on Data Literacy and educated leadership on the importance of investing in both direct and indirect value generators for the organization
Q: What are your top data priorities: business growth, data security/privacy, legal/regulatory concerns, expense reduction…?
- Business growth will be major data priorities, but for that to happen you expect data that can be trusted, highly secure and gaining the confidence of the customers and making them feel their data is safe and secure
- Improving operational efficiencies can eventually be an indirect factor for business growth
Q: Have you developed a business driven data strategy; is there support for it and is your Organization becoming more data-driven? What steps are you taking to ensure all areas of the business are data driven?
- Yes, I have been developing business drive data strategies across multiple organizations over the years. As a CDO I have the responsibility of gaining the support from the right stakeholders within the organization
- A common challenge I encountered while gaining support is helping the business leadership understand the value proposition. Everybody comes in with a “What’s in it for me?” mindset and I as the data leader have the responsibility of explaining the benefits of investing (and not investing!) and supporting the data strategy
- Steps I have taken to ensure I focus on all areas of business are the following
- Understand the most impactful area from which you can get catalysts to your initiatives
- Identify low hanging fruits with quick easy wins
- Prioritize your areas of focus. Remember none of us can do everything at the same time
- Show the business stakeholder what they get from this. This is highly critical
- Communicate, Collaborate, Coordinate and Educate
Phanindra Pydimarri – Senior Director of AI & Advanced Analytics at Stanley Black & Decker
Phanii is a Global Data Analytics Leader with over 15 years of experience in end-to-end Data Management with key focus areas in Data Strategy, Data Analytics, Data Science and transforming organizations into data-driven culture.
Phanii started his career as a BI Consultant, traveling across the US and working for various clients in different industries. He is a strong believer of economies of scale, is outcome driven and is passionate about solving key business challenges by using Data as a key corporate asset. He has strong experience using Data Science to improve key operational challenges and have experience standing up Data Governance programs across various public and private sector organizations. Over the years, Phanii has transformed cultures and showcased data as a value-added resource that can be leveraged to deliver measurable improvements at Bose Corporation, Sabre Corporation, Dallas Area Rapid Transit and many other global organizations.
Phanii is currently working as the Senior Director of AI & Advanced Analytics at Stanley Black & Decker.