A Recipe for Success in Transformation

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Starting a transformation program can be daunting, but with the right formula organizations can deliver real business value.

There’s a commonly cited industry statistic that states 70%1 of transformation programs fail. With the odds of failure greatly outweighing those of success, how can organizations confidently begin an automation and innovation discipline that delivers real business value? While every organization is different, there are a few common ingredients required in any transformation recipe.

People – assigned, aligned and accountable

In our previous article, titled “Automation and Talent: Not an “Either or” Decision,” we explain how talent is one of the most critical ingredients to a successful transformation program. Identifying the right people to lead and support your transformation program, as well as aligning their focus on business value and holding them accountable for meeting objectives are all essential first steps.

We believe there are three core disciplinary components of an effective transformation team:

  1. Build a multi-disciplinary digital business team, or fusion team,2 that sits horizontally across the organization. These teams provide a comprehensive perspective through a shared business objective and can identify common challenges in areas like reconciliation, data ingestion and anomaly detection that can be solved by optimized digital solutions. Because of their holistic vantage point across complex programs, this core team can ensure solutions are designed with maximum re-usability.
  2. Appoint a dedicated IT team skilled in emerging technologies for transformation projects. This IT team should be creative and approach problem solving through a clear lens, using new and emerging technology solutions to solve real business challenges surfaced and prioritized by the transformation team. Dedicating resources who are unburdened by ‘BAU’ operations and priorities, such as regulatory developments or maintenance, and holding them accountable to the horizontal business discipline, prevents the transformation agenda from being impeded.
  3. Align Subject Matter Experts (SMEs) who are responsible for achieving transformative outcomes as a primary responsibility. This can sometimes be the most difficult, but automation and innovation should not be passion projects or side gigs to existing operational duties. Leaders must incentivize through formal and informal channels, like with bonuses, goal-setting, and performance reviews. SMEs are vital in providing the business and industry knowledge that ensures the solutions which are delivered achieve the intended results.

The benefits of digital transformation compound when this three-pronged team of dedicated transformation analysts, IT and SMEs evolve from task-based automation to exploring the art of the possible and delivering next generation automation processes (See Figure 43) that not only provides scale and optimization but also higher value product and service opportunities.

Here we highlight how we automated a task to deliver next generation optimization of a business process.

This graph by Deloitte contains analytics of task-based automation and end-to-end automation. It shows that end-to-end next generation processes produce low volume but higher value opportunities. Alternatively, task-based automations produce a higher volume of lower value opportunities.  

Case study: Corporate Action payments

While we have a high degree of automation in the processing of payments relating to Custody Corporate Action events, there are still thousands of payments received that require investigation to ensure appropriate processing. Given the high value and compressed time cycles, this process can be resource intensive. Therefore, to improve this process, we focused a team of subject-matter-experts alongside data scientists to re-imagine the daily process using our AI/ML capabilities.

The result is our Corporate Action Payment Repair solution, which uses a neural network to predict matches of incoming payments to expected payments. This helped reduce over 80% of the manual input performed previously, allowing analysts to focus on solving high-complexity issues.


From our perspective, intelligent automation platforms made up of micro-services are accelerating transformation programs everywhere. Gone are the days of costly and time-consuming overhauls and replacements of legacy enterprise solutions. Automation platforms put capabilities into the hands of business users through a democratized approach. They support changing business dynamics, shifting client demands and evolving market dynamics. The plethora of options in the market can make choosing the right technology daunting. Many are focused solely on the technology, not the subject matter, and underdeliver by misunderstanding the desired business outcome. User configurable technologies bring innovative solutions closest to those who are best versed in the challenges that need to be solved.

Underpinning your technology stack with a clear data strategy that is pragmatic and solves business challenges is key. “Data fabric strategies will be essential for successful automation; however, data and process teams are not currently as collaborative as successful hyper-automation strategies will need them to be”4. Understanding where your data is coming from, its lineage, quality, and accuracy is critical.

An effective governance framework is essential for evaluating when to leverage an automation platform versus other technology solutions. Just as a multi-disciplinary team of IT and business experts can deliver automation, a similar approach can be applied to governance. This requires bringing together experts from Product, Systems, Data Management, Risk and Control to evaluate tool selection, data sourcing strategy, design, and scale through a repeatable and scientific governance program. 

Data-driven measures of success

Measuring productivity or reduction in FTE is often the default metric many transformation programs use to define program success. This can be problematic for various reasons. To improve productivity, firms aim to increase output while simultaneously reducing inputs – this can be achieved by automating manual work using RPA (Robotic Process Automation), for example, and simultaneously reducing headcount. However, this is an output-based approach, not an outcome-based approach. An outcome-based approach leads to longer term benefits such as new idea generation, improved client experience, and advanced analytics.

The following Seven Dimensions of ROI demonstrate how transformation can be impactful across many criteria. The impact of not pursuing a transformation can be detrimental.  

This image shows the seven dimensions of ROI in transformation including:

  1. Enabled Capacity - Unlock capacity through automation or allow for absorbing new processing volumes without increasing headcount.
  2. Simplified Architecture - Reduce integrations/ support needs for external providers by adopting a centralized solution
  3. Reduced Development Costs - Increase time to market and mitigate demand on core IT teams by leveraging a commonly accessible automation platform
  4. Risk Reduction - Deploy additional layer of automated validations, checks and alerts (safety net) across the organization by designing next level risk mitigating processes
  5. Client Experience - Respond swiftly to unique client needs and turn bespoke requests into scalable products and services
  6. Accelerate Organizational Placement - Embed process standardization and automation into transition projects (lift-automate-shift approach)
  7. Workforce Upskilling - Allow business groups to operate their automation programs independently through a democratized automation approach

Once measures are agreed upon, progress and tracking should be highly transparent to the stakeholders and the organization.


Successful transformation must start somewhere, and in this case, it should be with an organization’s most important ingredient: its people. Combining a three-pronged team of analysts, IT experts and SMEs with an automation platform that puts the tools in the hands of business users is a promising foundation. This, together with a clear data strategy and an effective governance framework to determine which tools to use, and when, are the essential ingredients for effective transformation.

For more information and practical insights, contact your BBH representative and follow BBH Market Insights on LinkedIn.

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1 The ‘how’ of transformation | McKinsey
2 What Are Fusion Teams? (gartner.com)
3 Deloitte Insights “Automation with intelligence”
4 Gartner - Hyperautomation Insight: How Should I Address Hyperautomation in My Product and Service Strategy, August 2022

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