Summary:
– Greg Holmes, Field CTO for EMEA at Apptio, emphasizes the importance of financial rigour in scaling intelligent automation.
– Successful pilot programs often fail to translate into sustainable enterprise-wide deployments due to initial financial modelling oversights.
– Integrating FinOps capabilities with automation allows for proactive cost management and value engineering, leading to better scaling outcomes.
Article:
Greg Holmes, serving as the Field CTO for EMEA at Apptio, which is now a part of IBM, underscores the critical role of financial discipline when it comes to expanding intelligent automation initiatives. While the “build it and they will come” approach may work for some technologies, automation requires a more strategic financial approach to ensure long-term success. Many executives have experienced the disappointment of successful pilot programs that fail to scale effectively across the entire organization due to initial financial models that did not account for the complexities of production scaling.
Holmes advocates for a shift in mindset by integrating Financial Operations (FinOps) capabilities with automation. This integration enables a transition from reactive cost management to proactive value engineering. By tracking resource consumption metrics from the outset, such as cost per transaction or API call, engineering teams can make informed decisions right from the beginning, rather than waiting months or years to assess the value generated by the automation.
One key aspect highlighted by Holmes is the importance of understanding the unit economics of scaling intelligent automation. Many innovation projects face a high failure rate, often due to financial opacity during the pilot phase masking future liabilities. By tracking marginal costs at scale and monitoring unit economics, organizations can ensure that as they grow, their unit costs decrease, leading to more efficient operations. Holmes cites a case study from Liberty Mutual where implementing consumption metrics led to significant cost savings.
Addressing legacy debt and budgeting for the long term are also crucial considerations when scaling intelligent automation. Organizations burdened by legacy ERP systems must decide whether automation serves as a band-aid solution or a bridge to modernization. Holmes stresses the importance of a total cost of ownership (TCO) approach to assess the full lifecycle costs of automation projects. By balancing variable costs with long-term commitments and strategic investments, organizations can scale automation effectively without facing the volatility that often derails transformation efforts.
In conclusion, Holmes advocates for a collaborative approach between technology and finance departments to ensure successful scaling of intelligent automation projects. By adopting a common language through frameworks like Technology Business Management (TBM), organizations can bridge the gap between operational metrics and financial accountability. This approach not only optimizes the scaling process but also fosters a culture of transparency and alignment across the entire organization.
