Large Scale Ambition
While Vanguard recognizes the importance of robust analytics, none of the company’s key initiatives have been centered on analytical capabilities. Still, as a largely virtual company (retail clients are rarely given the occasion to meet with representatives face-to-face) the opportunity is obvious. However, Vanguard remains committed to meeting client needs through more traditional means like expanding call centers rather than turning certain business functions over to analytics enabled automation.
Stages
It is difficult to say how Vanguard approached analytics before I arrived. What I have seen is the company progress from Stage 2 to stage 3. Since I have spent my entire career in the retail investor division, my perspective will be based on that part of the business. I believe this will be sufficient for the purpose of this paper given the division alone has about 5,500 employees and manages $1.9T in assets and accurately reflects the position of the overall organization.
Stage 2
Competing on Analytics describes Stage 2 competitors as possessing “localized analytics” and that is an apt description of what I found when I joined Vanguard in 2006. Any analytics in the retail division were isolated to our call center operations who were able to (somewhat accurately) forecast call volumes and manage resources through data models and visualization tools. From a client management standpoint, our IT group was still building many key elements of our homegrown CRM system and most client “intelligence” was gained and retrieved through very manual efforts. Mail processing was managed digitally but lacked any insights (at least none that were shared with client facing employees) on what was being received or what impact those trends may mean for the business. Many questions were being asked at all levels about how to be more efficient or better informed about clients but there was a shortage of expertise to actually take ideas to maturity. Stage 3 The retail business has made significant strides in the last few years. …show more content…
Call center operations is using more sophisticated models to improve forecast accuracy and better understanding and utilization of operational levers that increase efficiency and flexibility. Client facing crew now have access to more robust and sophisticated client insights that are easily accessible and drive better results from client contact. Mail operations are in the early stages of integrating robotics and AI applications to more efficiently handle routine requests. Today, the retail business is deploying analytics in all facets of the business yet there still does not appear to be a cohesive strategy with an “enterprise-wide perspective” necessary to achieve Stage 4. However, retail analytics roles are being expanded and centralized in an effort to take this next step towards becoming a true analytics competitor. Competitive Advantage As stated earlier, Vanguard’s most durable competitive advantage stems from its unique corporate structure and in turn, the ability to offer superior fund performance (92% of funds outperformed peer averages at the lowest possible cost (average expense ratio of 0.18% versus industry average of 1.01%) (Vanguard, 2017). This combination has resulted in ever increasing cash flows and, in 2016, Vanguard led the industry with nearly $200B in new money (Marriage and Pooley, 2017). While this success in of itself does not rely on analytics, various levels of business intelligence and analytics enable the optimization and sustainability of this advantage. For example, as mentioned in Competing on Analytics, Vanguard indirectly uses analytics through partners hired to manage fund portfolios. These firms use proprietary models in their active management strategies at lower cost than more traditional methodologies. This allows Vanguard to house a broad array of actively managed products while staying true to their low cost philosophy. Although Vanguard has had success with their active management sub-advisor strategy, Vanguard is primarily recognized for its index products. The performance of these funds relies on the indirect and direct use of analytics to create a competitive advantage. Indirectly, Vanguard works with index providers to sample some portion of the stock or bond market. In other words, the index is an analytical model that identifies securities that match a set of desired characteristics and the proportion those securities represent in the specified market segment. More directly, Vanguard uses analytics to track and replicate these indices. This is
While Vanguard recognizes the importance of robust analytics, none of the company’s key initiatives have been centered on analytical capabilities. Still, as a largely virtual company (retail clients are rarely given the occasion to meet with representatives face-to-face) the opportunity is obvious. However, Vanguard remains committed to meeting client needs through more traditional means like expanding call centers rather than turning certain business functions over to analytics enabled automation.
Stages
It is difficult to say how Vanguard approached analytics before I arrived. What I have seen is the company progress from Stage 2 to stage 3. Since I have spent my entire career in the retail investor division, my perspective will be based on that part of the business. I believe this will be sufficient for the purpose of this paper given the division alone has about 5,500 employees and manages $1.9T in assets and accurately reflects the position of the overall organization.
Stage 2
Competing on Analytics describes Stage 2 competitors as possessing “localized analytics” and that is an apt description of what I found when I joined Vanguard in 2006. Any analytics in the retail division were isolated to our call center operations who were able to (somewhat accurately) forecast call volumes and manage resources through data models and visualization tools. From a client management standpoint, our IT group was still building many key elements of our homegrown CRM system and most client “intelligence” was gained and retrieved through very manual efforts. Mail processing was managed digitally but lacked any insights (at least none that were shared with client facing employees) on what was being received or what impact those trends may mean for the business. Many questions were being asked at all levels about how to be more efficient or better informed about clients but there was a shortage of expertise to actually take ideas to maturity. Stage 3 The retail business has made significant strides in the last few years. …show more content…
Call center operations is using more sophisticated models to improve forecast accuracy and better understanding and utilization of operational levers that increase efficiency and flexibility. Client facing crew now have access to more robust and sophisticated client insights that are easily accessible and drive better results from client contact. Mail operations are in the early stages of integrating robotics and AI applications to more efficiently handle routine requests. Today, the retail business is deploying analytics in all facets of the business yet there still does not appear to be a cohesive strategy with an “enterprise-wide perspective” necessary to achieve Stage 4. However, retail analytics roles are being expanded and centralized in an effort to take this next step towards becoming a true analytics competitor. Competitive Advantage As stated earlier, Vanguard’s most durable competitive advantage stems from its unique corporate structure and in turn, the ability to offer superior fund performance (92% of funds outperformed peer averages at the lowest possible cost (average expense ratio of 0.18% versus industry average of 1.01%) (Vanguard, 2017). This combination has resulted in ever increasing cash flows and, in 2016, Vanguard led the industry with nearly $200B in new money (Marriage and Pooley, 2017). While this success in of itself does not rely on analytics, various levels of business intelligence and analytics enable the optimization and sustainability of this advantage. For example, as mentioned in Competing on Analytics, Vanguard indirectly uses analytics through partners hired to manage fund portfolios. These firms use proprietary models in their active management strategies at lower cost than more traditional methodologies. This allows Vanguard to house a broad array of actively managed products while staying true to their low cost philosophy. Although Vanguard has had success with their active management sub-advisor strategy, Vanguard is primarily recognized for its index products. The performance of these funds relies on the indirect and direct use of analytics to create a competitive advantage. Indirectly, Vanguard works with index providers to sample some portion of the stock or bond market. In other words, the index is an analytical model that identifies securities that match a set of desired characteristics and the proportion those securities represent in the specified market segment. More directly, Vanguard uses analytics to track and replicate these indices. This is