Over the last three weeks we have covered a myriad of issues that confront CDOs in the ever-evolving tech landscape. In the first part of our conversations, Bharti Rai, the former head of data and digital innovation at Bayer and incoming VP of commercial effectiveness at Novartis, illuminated some of the challenges involved in picking the right vendors as a CDO.
In last week's segment, Rai and DATAx considered some of the inherent difficulties in understanding what is fundamentally required of CDOs in organizations which have typically never had one before.
This week, we conclude our series with Rai by discussing some of the deeper challenges she believes women face in STEM careers, how she believes they need to be addressed in order to propagate true change:
Inclusivity in STEM starts way before individuals enter the workforce and industry. It is rooted in cultural aspects, in how we raise our boys and girls and the unconscious, unintentional decisions we make when exposing them to certain after-school activities.
My daughter is six years old and loves building Legos (probably due to watching her two older brothers while she was growing up). I found a Lego group for her, but even at her young age, there is already a majority of boys in the group. On the other hand, her dance classes are filled with girls. They (and we) receive subconscious messages on what activities are "girly" versus which ones aren't. If it starts young (and with no ill-intention), it is not surprising to see this trend continue through high school and into college.
Overcoming challenges in this area will take a cultural change, which will be slow. But if we can start by achieving equality in leadership positions (STEM or not), it would be a huge step forward. However, it will take guts from leadership to take concrete actions with definitive measurements and unambiguous accountability to make any of this happen.
To conclude, we asked Rai about her insights regarding some of the trends she predicts AI to take in the life sciences industry going into 2019:
Patient adherence is a big factor in improved patient outcomes.
According to the recent 2018 Medisafe Annual Adherence Index, it is estimated that only 50% of patients correctly follow their medication regimen. If AI can predict factors leading to drop-offs and help intervene at the individual patient level with the appropriate care at the appropriate time, it would elevate the quality and effectiveness of patient care.
AI and ML can also greatly impact the identification of difficult-to-diagnose diseases or detect worsening severity in patient symptoms and thus intervene with the appropriate level of patient care. So far, companies have dabbled in AI/ML, either through in-house data scientists or, more likely, through external expertise in predominantly isolated projects.
In 2019, I see companies solidifying their approach and commitment to AI/ML and starting to put some investments toward building out these capabilities, either in-house or in a partnership model.
Bharti Rai will be on a panel on Day One of the Chief Data Officer Summit, part of DATAx New York, taking place on December 12–13. To attend and hear more great insights from other CDOs from some of the biggest and most influential organizations, register here today.