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    • THE AI-FIRST CEO/ CXO
      • Why AI must be CEO-led?
      • GenAI CoE Org Structure
      • CEOs Choose Right AISPs
      • SPs of AI-Powered CEOs
    • Platform Engineering: How
      • How to Win on Platforms?
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      • What's your AI story?
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      • Unique AI stories: How to
      • Checklist: AI Narrative
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HOW YOUR SP PARTNERS MAKE YOUR PLATFORMS WIN

If you automate a mess, you end up in a bigger mess! - Top 5 Next Practices to prevent it....

Client businesses, even the traditional ones like manufacturing, or highly regulated ones like BFSI and healthcare, are getting rapidly platformized, thanks to the push to Everything Digital, from the users, customers, suppliers, partners, citizens, regulators- basically all key stakeholders and markets. 


GPT-augmented explanation of Platformization of Business:


 What is platformization of businesses? A platform is a collection of digital services that can be integrated into a company's business processes and functions . Platformization means  that your entire business can be digitally integrated , either directly or via software that runs on multiple clouds  and devices.  


Platforms range from deep tech ones like the Google, Microsoft, AWS, IBM ecosystems, to business operations workflows and functions platforms like ServiceNow, Workday, Salesforce and so on.

All end-user companies working on massive digital transformation programs are leveraging SP (Service Provider) partners to make best use of their investments and efforts onto these platforms.


How do they ensure best value for their money, from the platforms and their implementation partners?


Here are top 5 next practices to work on:



  • Ability to Automate the Hyper-automation: e.g. quality, impact and no. of IPs on accelerators to rapidly deploy and modify/ enhance workflow automation modules and prebuilt workflows


  • Ability to move Dumb Process Automation to Smart Machine-first/ Autonomous: RPA to Intelligent Self-learning self-augmenting bots/ workflow automation agents


For example: Static/ deterministic rule-based rigid RPAs => dynamic ML-powered integrated intelligent automation => deep-dive knowledge-based real-time smart automations with auto-governance and auditability/ compliance (also scanning for regulatory changes in knowledge sources, and updating rule-bases for risk management, audit, continuous compliance). 


Example use cases: Autonomous escalation management and priority 1 resolutions, critical errors/ failures prediction-prevention-preemption-corrections, continuous improvement of service quality across business and IT, continuous UX CX enhancements etc. 


  • Ability to Verticalize and Contextualize by regions: Business logic and hence rules and workflows vary by verticals, GRC requirements also differ by verticals and regions. 


Relevant regional vertical peer group reference-ability and case studies are key indicators of this ability.  


  • Ability to cross-pollinate across verticals, wherever apt: e.g. k-base sharing use cases on patterns or anomalies in fraud. error, noncompliance, leakage, CX/ UX, productivity shrinkage. 


Most common example of customer profile and creditworthiness for instance- for financial behavior predictive models applicable in different verticals like BFSI, retail, e-comm, media... 


  • Actions on ESG: e.g. making business workflows greener beyond just IT infra and cloud, to build best practices alongside verticalization 


For example- carbon efficient workflows for net zero banking - cost of both operations and innovations will come down this way. Social and STEP impact will also create great storyboards for clients. 

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