Co-creating AI vision, architecture & operating model for a sustainability major
We are navigating in the dark, struggling with disjointed systems and manual processes. Even with all the investments in data, making informed decisions is getting difficult.
CDO, WASTE MANAGEMENT FIRM
Client Situation
- A leading sustainable waste management firm set an objective to grow faster than industry, with increased investments in digital and data infrastructure. However, after a few years of investments, the company hasn’t been able to unlock true digital acceleration, speed to roll out capabilities is still slow, and RoI is questionable, and how to enable AI capabilities is unclear.
- Our rapid diagnostics, which were used as an input in our AI
vision workshops with all cross-functional stakeholders uncovered following
priority problems to be solved:
- Data quality & richness: They had limited internal data sources, and the quality of data wasn’t consistent across all functions. The insights weren’t credible
- Functions had started to build their own point AI solutions with disparate technologies, which were designed for functional not enterprise optimization, and were poorly integrated and managed, increasing tech debt.
How we added Value
- AI vision & roadmap: With our rapid diagnostics, and a carefully curated art-of-possible, we worked with cross functional teams through series of workshops to build a prioritized view of the business problems that needed to be solved, and the underlying technology & process capabilities that needed to be upgraded to support these business problems. This was the roamap for the enterprise.
- AI operating model: We also created a federated operating model, defining the collaboration and support between IT and business: IT providing toolset and capabilities and business defining applications and process changes.
- AI Toolset: We rolled-out an enterprise AI studio on our Damia platform, fully integrated with enterprise data & digital fabric, and with a prebuilt set of capabilities & business applications. We also trained IT teams, under a co-development model, to rapidly develop new business & data engineering features and capabilities on the enterprise AI studio.
Impact
3x richer data
90% higher quality data
5x Increase in speed of development of new apps & capabilities
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