ConvergeHEALTH by Deloitte

Managing Director

Vice President Of Product Development

Senior Product Manager

Deloitte

Healthcare & Life Sciences/Deloitte Consulting Innovation Practice
- Healthcare Technology Products
- Health Information Management
- Health Informatics
- Strategy and Planning

Senior Manager

Beckman Coulter, Inc.

Corporate Strategy Planning
- Competive Strategy 
- Business Planning
- New Market Entry

MBA Intern - Corporate Strategy Planning

Tata Consultancy Services Ltd.

IT Consultant
- Analysis\Design\Development of IBM ISeries software

IT Consultant

Current - Managing Director at ConvergeHEALTH by Deloitte. 

I have two decades of hands-on experience in all aspects of enterprise software: business strategy, technology implementations, product management, and software engineering. 

In my current role, I focus on building high-growth enterprise software products and creating effective team-based software engineering operations.

I have authored a book, Becoming a Software Company, that describes principles for non-software enterprise companies to think and operate like software companies.  

I have an MBA from the University of California, Irvine, and an engineering degree from Thapar University, Patiala, India.

After an amazing stint of almost 16 years at Deloitte, I am moving on. My last day was this past Friday, 4/26.

For the next phase, I am starting Innowaring Labs, a service business (to begin with) that will help enterprise organizations maximize the business impact of their technology investments and teams. (More details to come).

Deloitte was a wonderful and career-defining experience. 

It offered me rich and varied opportunities—strategy, data and analytics, big implementations, product development and management, and building and managing hybrid software businesses at ConvergeHEALTH. I got to execute every possible role as a practitioner to learn the art and business of enterprise software. I summarized that in a book published last year (Becoming a Software Company).
  
The book was a manifesto of sorts—a set of principles for building innovative user-centered software systems. Writing the book and my work over the last several years have convinced me that the limiting factor to business growth in the age of software and AI isn't the technology itself—it is the art of management. 

Considering the above limiting factor, Innowaring is an adaptive management system to create new business value in the age of software and AI - focused on customer impact, optimized for business agility, and driven by a people-first mindset. Innowaring Labs is designed to help organizations implement Innowaring strategies and practices in ways that make the most sense for their business. 

In summary, I am leaving Deloitte to put my money where my mouth is, to align my work with my core professional beliefs.

In the coming days and weeks, I will share more details on Innowaring Labs, the services offered, and how we can work together. If you are interested and the theme of innowaring resonates with you, please follow me on LinkedIn. 

In the meantime, I am available for the following:

 1) 1:1 Coaching—If you are in an enterprise technology innovation role, at any level, from executive to developer level, I am available to brainstorm ideas on strategy, ways of working, and reorienting culture.

2) Advising—If you are building a startup in the enterprise technology space, I can help you shape your strategy and offerings as an advisor or a board member. 

3) Consulting—If you run an enterprise technology organization, I am available for consulting engagements to enhance your organization's effectiveness and deliver business impact.   

If your need is aligned, please reach out via DM. Even if it isn't, but you have feedback, or there are other things we can collaborate on, I would love to hear from you. 

#technology
#management
#innovation

Amarinder Sidhu

Founder @ Innowaring Labs| Enterprise Technology Consultant | Startup Advisor | Author

Why is Innowaring an adaptive management system?

How can consulting enhance enterprise technology organization's effectiveness?

The news of the Walmart Clinics and Telehealth unit shutting down isn't surprising if you have spent time in the healthcare business.  
 
It isn't a stray event. Amazon Care shut down in 2022, and Walgreens recently took a $5.8 billion writedown on the VillageMD acquisition. There is enough evidence now that you can't solve primary care merely by throwing scale at it.  
 
Also, it is becoming clear that the low-acuity care access constraint isn't just a supply-side problem. Instead of treating doctors and nurses as fungible labor resources, as these retail clinics tend to, the better bet may be to empower clinicians to work with patients to solve demand-side challenges wherever it makes sense.

How important is primary care in healthcare?

What are demand-side challenges in healthcare?

Just as SaaS didn't eliminate custom implementation services, AI-powered software isn't going to either. 

There is some chatter in VC circles about how AI spells the doom for big consulting firms' implementation business. And how it opens up multi-trillion opportunity for new startups. Not so fast! 

A) No services firm, big or small, starts with a blank slate while implementing. Depending on the business area, there is always a piece of software to accelerate the implementation 50% or above. 

B) Services firms aren't sitting idle or oblivious to the shift happening. AI changes the dynamics, but packaged software has been changing the implementation business for a decade and a half now.
 
C) The new value in enterprise software has shifted up the stack, and packaged software has been verticalizing simultaneously. Virtualized infrastructure -> Specialized Databases -> Specialized Apps -> What's next with AI? Specialized user workflows, perhaps?

D) Lastly, vendor software doesn't equate to a final production system. Even though more becomes possible, the accidental complexity of putting together and managing systems escalates with every wave of innovation. It isn't getting any simpler when we start mashing APIs, models, training datasets, and new conversational interfaces together. 

#technology
#management
#innovation
#ai

Earlier this week, I spent time with a healthcare AI startup building a curated clinical reference database for AI decision support in primary care.  
 
They were early, but their eventual deployment approach was partnering with services organizations to implement within medical practices and organizations.  
 
However, I think a better strategy for enterprise tech in a focused use case like this is building your lean services organization. 
 
Because, in cases like this, it is possible to make implementations much less labor-intensive and playbook-oriented and to own your tech's last-mile customer experience.  
 
#technology 
#management 
#innovation 
#enterprisesoftware

What impact can a lean services organization have on enterprise tech?

How important is decision support in healthcare AI?

𝗤𝘂𝗮𝗻𝘁𝗶𝗳𝘆𝗶𝗻𝗴 𝗧𝗵𝗲 𝗜𝗻𝗻𝗼𝘄𝗮𝗿𝗶𝗻𝗴 𝗢𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝘆: 𝗙𝗶𝗹𝗹𝗶𝗻𝗴 𝘁𝗵𝗲 $𝟭.𝟱 𝗧𝗿𝗶𝗹𝗹𝗶𝗼𝗻 𝗛𝗼𝗹𝗲  
 
Enterprise software lurches forward from transformation to transformation.  
 
The promise of large transformations launches countless software sales and enterprise implementation programs. 
 
But do such technology transformations translate into consistent business transformation?  
 
No. Many studies estimate that 70% to 95% of large transformations fail to achieve the intended business outcomes.  
 
Even taking the low end of that estimate, the potential waste from global enterprise transformation spending is estimated at $1.5 Trillion.   
 
In an era where business innovation is synonymous with technological innovation, closing this gap between intended and actual business outcomes represents an enormous opportunity.  
 
I call it 𝗧𝗵𝗲 𝗜𝗻𝗻𝗼𝘄𝗮𝗿𝗶𝗻𝗴 𝗢𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝘆 - evolving management systems in ways that allow every enterprise to realize the transformational business impact that the software revolution represents. 
 
#technology 
#management 
#innovation 
#innowaring

How can enterprises leverage the Innowaring Opportunity for business impact?

What are the key factors influencing the success of technology transformations?

What role do management systems play in achieving business transformation?

One insight from systems thinking helped me become a better manager more than anything I have known or understood.

Optimizing information flow within the software work pipeline matters much more than highly scientific management of work, resources, and people. 

To understand, see the attached visual. A pipeline of work is a combination of stocks of work (rectangles) with the information flow (arrows). 

A manager's primary objective should be to make various information loops as tight as possible to reduce the cycle time of decisions.  

Instead of trying to account for every requirement, your teams should be able to start with well-understood ones and get informed with customer feedback as soon as possible. 

Instead of being held to a single deadline estimate, your teams should be able to build trust, credibility, and confidence with the soonest possible delivery and deliver many times before the final deadline.  

Instead of committing to upfront team design and composition, you should gradually grow the team and be flexible in adjusting based on what you learn from information loops. 

Lastly, you should share these team and work decisions with external stakeholders often and early. I have learned that being transparent is the best way to deal with unwanted outside pressure. 

This isn't easy, especially in highly political environments, but it is worth trying. Even in hopeless situations, making the information flow improves the messiness and decreases stakeholder tensions. 

I hope thinking of work as stocks and flows and optimizing flows helps you as much as it has helped me. 

#technology
#management
#innowaring
#systemsthinking

What is the significance of optimizing information flow in management?

How can systems thinking enhance managerial effectiveness?

Why is prioritizing customer feedback crucial in work management?

Stock and Flow_Software Development

Is this aligned with our strategy? 
 
This question isn't very helpful when making technology portfolio decisions within large organizations. 
 
In such organizations, the "strategy" usually isn't defined in specific enough terms to evaluate the choice. Also, it tends to reduce the alignment to a one-shot exercise.  
  
A better question to ask is:  
 
What is the novel and specific insight into the customer or market problem triggering this investment need?   
 
This question brings the right level of specificity and a continuous evaluation mindset into the discussion.  
 
It will make you consider a specific bet on the future versus making a general trend-oriented decision.    
 
#technology 
#management 
#innovation

How can technology portfolio decisions benefit from customer insights?

How does focusing on specific bets impact innovation in technology portfolios?

What role does continuous evaluation play in technology portfolio decisions?

So neat! 

I have often wondered that one ought to be able to make better use of the water from the dehumidifier. This is it.

How does impact investing contribute to sustainable development?

What opportunities does UpLink offer for innovative solutions?

What are key strategies for achieving Sustainable Development Goal 6?

These machines can create clean water from thin air, even in arid regions. 💧

What’s your innovative solution for empowering the world’s most vulnerable communities? Submit it to UpLink for a chance to join a community of partners, innovators and investors who can help scale your start-up: https://wef.ch/3UGM5kY 

HCLTech HCL Enterprise
UpLink - World Economic Forum IKEA Foundation U.S.Government Convergence Blended Finance Roots of Impact Bill & Melinda Gates Foundation Conrad N. Hilton Foundation elea FMO - Dutch entrepreneurial development bank AfricInvest Group African Development Bank Group Health Finance Coalition Water.org WaterEquity 

#HRI #frontiermarkets #impactinvesting #water #SDG6

What are some tips for working with 10x developers?

How important is remote work in the tech industry?

Co-Founder, Ensemble | UT Austin, CMU and Ex-Workday, Oracle, Veeva

If you are based in the US, are a top 1% full-stack developer with expertise in reactjs, love working with other 10x developers and are looking for an opportunity to transform application development forever, DM me. 100% remote.

This perspective below from Michael Bolton is solid! 

Tech is progressing fast. But something else is progressing even faster: needless tech boosting; a lot of tech amplifying without the context of what problem it solves, for whom, in which context, and how.

It's imperative to have good ways to critically evaluate the hype narrative.

What impact will AI have on the workplace?

How can software evaluation help in assessing AI products?

I help people and organisations find product problems and solve testing problems quickly and expertly with Rapid Software Testing. developsense.com / rapid-software-testing.com

The producer of practically every product or service on the market seems desperate to surf the AI hype wave these days. It seems the big thing is to claim the product to be “AI-enabled” or to have “AI features”.

Here’s a quick and (mostly) easy way to evaluate claims about AI products. (I’ll say “product” to save saying “product or service” every time.)

1. Try replacing “AI” with “software”, and see if there’s any material difference in what’s being said, offered, claimed, or advised. (That is: is this just software, developed as usual, that has a few somewhat mysterious and clever features? Lots of "self-healing" testing tools seem to do things easily accomplished by good old-fashioned nested IF statements.)

2. Now try replacing “software” from Step 1 with “software that was written without a skilled human designing, reviewing, or even understanding the resulting algorithm”, and ask yourself if there’s anything you might be concerned about.

3. Finally, take the result from Step 2 and add “and without monitoring or reviewing the output from the algorithm”.

4.  Take the results from the first three steps and ask “What could go wrong, and how would we find out about it?”

If the answer to (4) is 

a) “nothing that causes harm, damage, or diminished value; nothing that involves loss of life, health, safety, money, data, reputation, freedom, opportunity, rights, or brings significant risk related to any of those; and 

b) if there were such problems, we’d know right away, before it’s too late” 

then we might be okay, and not on dangerous ground.

Finally, Step 5.

5. To what degree is the answer from (4) supported by experiment, experience, and exploration from a critical stance? (That is: has the claim been tested? Is there evidence for it? Or is it more like a wish, or a marketing slogan?)

Some follow-up to Step 5 in the post linked below.

And if you find this helpful, I wouldn't exactly be upset if you reposted it for more reach.  Thanks!

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