A few months ago, NetApp Healthcare’s AI principal, Esteban Rubens, shared an insightful post, Data science as a service in healthcare and life science: Control shadow AI. During the weeks following, Esteban suggested that as a former healthcare CIO I also share my perspective on shadow IT. I jokingly responded, “Herding cats.”
Having had some time to reflect, I’d say that a more accurate title for my colleague’s blog might have included both the words “control” and “enable.” At one time in my career, I believed that IT and only IT should oversee technology initiatives. But now I am a convert. Turning covert, shadow IT into overt, business-managed IT can be quite positive when it’s aligned with the IT department.
My grandmother, Leola, used to say to me, “You catch more flies with honey than vinegar.” So it is with the sweet enablement of shadow IT versus the vinegary approach of eliminating it.
Shorter timelines, autonomous budgets, lack of confidence in IT, and separate organizational leadership structures are often cited as the reasons for rogue IT procurement. Most digitally transformed CIOs realize that shadow IT can indicate that IT isn’t delivering what the organization needs. They seek to understand the business challenges and problems that lead to shadow IT, and they acknowledge that IT having full control over tech spending is the vinegar of the past. Of course, these evolving leaders aren’t blind to the risks introduced by shadow IT; they take precautions while encouraging organizational innovation. But adapting IT to become a strategic business partner is the proverbial honey.
The healthcare industry has enough problems—it’s plagued with high costs, poor outcomes, nursing and physician shortages, preventable medical errors, and other major problems. Healthcare CIOs need to provision modern IT infrastructures so that they maintain data security while allowing healthcare data scientists to capitalize on the proliferation of no-code and low-code analytics tools. This approach optimizes IT investments and lets you deliver actionable insights faster.
NetApp® has been helping healthcare organizations deploy data science as a service (DSaaS) for years. And we’ve refined a process that’s optimized for speed, accuracy, and customer satisfaction. For a description of our approach to DSaaS in an academic setting, read Data Science as a Service—Prototyping an integrated and consolidated IT infrastructure combining enterprise self-service platform and reproducible research.
Adding machine learning operations (MLOps) tools rounds out the offering by helping data scientists automate, streamline, and speed up feature engineering, pipeline deployment, continuous integration/continuous deployment, and model monitoring.
To learn more, read our technical reports TR-4834 and TR-4841. You can also visit netapp.ai to learn more about our AI solutions.
If you would like to start a conversation about data science as a service, contact your NetApp sales team or your NetApp partner, or get in touch with us.
Lisa Hines is a healthcare CIO on NetApp’s Global Healthcare and Life Sciences Team. Her 25 years of real-world experience in the industry allows her to deliver strategic insights and strategic planning for customers and partners.
Throughout her career, she has led numerous early adopter projects in the healthcare provider space and has participated in statewide collaborative efforts to improve access to high-quality health care, while effectively managing the cost of providing care.
She is an active HIMSS member and has held numerous board positions in her local chapter. In her spare time, Lisa enjoys lake life, kayaking, and standup paddleboarding.