Michael Del Priore
Technology Advisor and Consultant
Michael Del Priore is a technology change leader, consultant, and former CIO to several of the world’s leading CPG, Pharma, and B2B companies. He has proven his expertise in digitizing business processes, with specific experience in Manufacturing, Supply Chain, Commercial, and Financial Management.
As a CIO and trusted advisor to several C-suite executives, he has successfully integrated many acquisitions to support his companies’ growth agendas and leveraged technology to drive growth and profitability.
Throughout his prolific career, Michael has shared his success with leading CPG, Pharma, and B2B companies, including Diversey, Catalent Pharma Solutions, Church & Dwight, Roche, Philip Morris (Altria), and Accenture.
Hello Michael! You’ve served as a senior technology leader in global life sciences and consumer goods companies. Can you share some similarities, challenges, and how technology plays a role?
A very interesting question. One would think they are quite different industries, but there are a number of general similarities between them, especially in the commercial areas. For example, both industries are regulated, typically have indirect distribution and large sales forces, and utilize external market data sources to drive sales and marketing activities. In fact, when I was recruited to Roche, my CPG commercial experience was a key factor in my selection.
Both industries rely heavily on technology to support their commercial processes. CRM solutions drive the go-to-market activities across different market segments and correlate internal and external data to identify opportunities in the marketplace. Key account management is vital to understanding the full set of interactions with their best customers.
On the manufacturing side, pharma regulations drive heavier requirements that demand more sophisticated technology solutions to support quality control, batch record documentation, and manufacturing analytics. These are required in consumer products as well, but not to the same degree.
Digital transformation has been a hot topic, receiving considerable investment, particularly before COVID-19. Are the approach and key objectives consistent across both industries?
I think digital transformation needs to focus on the areas that drive improved company performance. Start with the processes that drive revenue and costs. This identifies the activities that will improve how the company operates. It is specific to each company, so I think we would see both similarities and differences across the industries depending on how mature the company is.
How do you measure the success of a digital transformation initiative?
I like to focus on the metrics for specific business processes – can you reduce cycle time and the labor cost to execute key processes while improving the business metric? For commercial processes, I have used a number of sales calls per cycle as a productivity measure. Projects we executed eliminated or automated the administrative work of the sales rep to drive higher call rates. A financial example would be accounts receivable – automate the process to collect cash faster with less people leading to improved cash flow. A third example would be automating the manufacturing process to reduce deviations and waste thereby improving quality and lowering manufacturing cost.
Machine learning and AI are ubiquitous in today’s IT discussions and most corporate strategic road maps. How do you see its importance and future importance?
I think it will be very important going forward, but perhaps the hype is too high right now. Many of the technology companies that I have worked with for years are now AI companies.
I look for opportunities where technology can augment and support the human activities at the company. I recently worked with a next-generation manufacturing execution systems (MES) software company that leverages AI to automate processes. MES software is designed to optimize the manufacturing process by seamlessly monitoring, tracking, documenting, and controlling the entire production lifecycle. With the addition of AI and machine learning, we can optimize these production cycles to be even more effective, improve quality control, reduce inventory and costs, and, most importantly, be predictable. The benefit of AI predictive models is to optimize yield and reduce deviations, putting your team in control of risks before they occur.
You and your son are playing a fair amount of high-level golf during your semi-retirement. How’s your game, and what tips do you have for our readers to improve their game?
My game is pretty good now. I maintain around a five handicap. I don’t hit it very far anymore, but the other facets of my game have improved. Just last week, my son and I competed in the Carolinas Father/Son Championship. It is an alternate shot format that is challenging and requires excellent teamwork. We had a great time and shot even par to tie for third place in our flight.
My advice for golfers is to practice regularly with purpose and find a professional you trust to help fine-tune your technique and lower your scores.
Thank you Michael for taking the time to share your thoughts with us today.
Thomas Buckley
Chief Executive Officer
StayinFront
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