Background
As generative AI recently took the world by storm, there is lot of discussion on how we can create private large language models for enterprise use to meet regulatory, compliance and legal requirements. According to Gartner reports, Generative AI has already been used to design drugs for various uses within months, offering pharma significant opportunities to reduce both the costs and timeline of drug discovery. A truly intelligent and sustainable enterprise is composable and is based on 3 principles and new value chain framework:
The three building blocks of composable business are:
- Composable thinking, which keeps you from losing your creativity. Anything is composable. When you combine the principles of modularity, autonomy, orchestration and discovery with composable thinking, it should guide your approach to conceptualizing what to compose, and when.
- Composable business architecture ensures that your organization is built to be flexible and resilient. It’s about structure and purpose. These are structural capabilities — giving you mechanisms to use in architecting your business.
- Composable technologies are the tools for today and tomorrow. They are the pieces and parts, and what connects them all together. The four principles are product design goals driving the features of technology that support the notions of composability.
As there is a need for looking into value chain from triple bottom line and sustainability angle , Gartner thinks our outdated business value chains needs refreshing to create a multi-factor value chain.
Multifactor enterprise value takes continuous account of a range of material variables and value levers, enabling you to balance the value you deliver to stakeholders with the value you realize in return. This approach provides the visibility decision makers need to create opportunity, sense and respond to the critical demands of stakeholders and iterate against multiple factors as conditions change.
To employ a multifactor approach to enterprise value, you first have to listen to stakeholders so you can identify — despite the breadth, urgency, pace and volume of issues and concerns — what is material to them and you. You also need to monitor for fast-moving, high-impact disruptions.
This may require new listening mechanisms, as many organizations lack transparency on those critical elements of nonfinancial performance that are indirect but leading indicators of long-term value. You also need to measure where efforts to create value will not actually realize the intended value. This is where Intelligent Sustainable Enterprise and Enterprise DevOps will help to accelerate the new value chain.
Intelligent Sustainable Enterprise Capability Model
The fun part of this is to execute this abstract principle in large and complex transformation programmes ex : SAP. In addition to the solution complexity, the idea of composable Devops makes a lot of legacy SAP consultants and SAP CoE consultants nervous to an extent that they think it is impossible to move to real DevOps model in future especially in a SAP landscape as redesigning ERP processes can be very risky, costly and complex. The fit to standard and clean core for SAP and NON-SAP COTS products principles makes it a bit simpler [unless there is business value] but data and integration becomes the nightmare if the innovation at edge apps are not designed carefully.
While there is lot of theory on moving to Intelligent Sustainable Enterprises, I don't think we have capability map on what an intelligent sustainable enterprise should look like and hence I want to share the rough sketches of Intelligent Sustainable Enterprise for Pharmaceutical Industry with my beloved SAP community members to exchange more ideas and perspectives on how we can turn this great future into reality in SAP transformation projects.
User Stories
Do we now think, the above capability model will help us to deliver below user stories for a pharmaceutical industry in an SAP transformation project:)?
User Story 1: AI-Powered Eco-Friendly Personalized Medicine
Persona : As a medical oncologist at a leading hospital, I want to leverage SAP-powered AI algorithms to optimize cancer treatment plans for my patients.
User Story Description:
- I need to analyze complex patient data, including genetic profiles, medical history, and treatment responses, to tailor the most effective treatment plans.
- I can access vast amounts of medical literature and clinical trial data, staying updated on the latest evidence-based treatment options.
- I ensure the accuracy and reliability of treatment recommendations, enhancing patient outcomes.
- Eco-friendly treatment options by integrating data on sustainable pharmaceutical therapies, aligning with our company's commitment to environmental responsibility.
- I can visualize and interpret treatment outcomes, allowing for continuous improvement in personalized medicine over time.
User Story 2: IoT-Enabled Medication Adherence
Persona : As a patient managing chronic conditions, I want to leverage IoT-enabled medication adherence tools integrated with SAP solutions to ensure I take my medications as prescribed.
User Story Description:
- I need a user-friendly IoT device that seamlessly syncs with my smartphone, providing real-time reminders and notifications to take my medications.
- By integrating IoT devices, I ensure secure and efficient data transmission between the device and my mobile app.
- I should be able to process medication adherence data, allowing me to share this information with my healthcare provider for better treatment management.
- I want to participate in a patient community encouraging medication adherence through gamification and rewards.
- Advanced Analytics capabilities allow me to track my medication adherence trends over time, empowering me to take an active role in managing my health.
- Adhering to my medication schedule, I can potentially avoid disease exacerbation, leading to reduced hospitalizations and contributing to the sustainability of healthcare resources.
- Ensure that my data privacy preferences are respected and adhered to throughout the medication adherence process.
- Medicine efficiency is monitored and reported back to the pharmaceutical industry
User Story 3: AI-Driven Clinical Trial Recruitment
Persona : As a clinical trial coordinator, I want to leverage SAP-powered AI algorithms to recruit eligible participants for clinical trials efficiently.
User Story Description:
- I need to identify eligible patients for specific trials from a large pool of potential candidates.
- I can process patient data rapidly, enabling real-time patient matching against trial inclusion criteria.
- I can securely collect patient consent and manage participant data while ensuring compliance with data privacy regulations.
- Advanced analytics capabilities allow me to identify diverse patient populations, ensuring inclusivity and representativeness in our research efforts.
- I want to collaborate with patient advocacy groups and raise awareness about our clinical trials and engaging potential participants effectively.
- Expedite clinical trial completion, leading to faster drug development and potential environmental benefits through quicker access to sustainable medical treatments.
- Ensure seamless data exchange between clinical trial systems, patient databases, and research organizations, streamlining the recruitment process.
- I can efficiently manage our clinical trial team, ensuring effective collaboration and communication throughout the research process.
- I need to ensure compliance with regulatory requirements and helps streamline the clinical trial process from patient recruitment to data analysis.
Will the intelligent and sustainable enterprise capability model help medical professionals to patients and researchers, to make informed decisions, drive efficiencies, and promote sustainable practices throughout the healthcare ecosystem:)? What are your ideas to change the way suppliers, employee and customers communicate? Does enterprise communication metaverse Facebook scare you if data flows seamlessly between industries?
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