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How to succeed with ambitious process optimization efforts

Thierry Kahane & Jan-Malte Praedel
Mar 13, 2024

Significant benefits such as tapping into additional sources of revenue, unlocking millions in savings, and enhancing cash flows are achievable through optimizing major business processes. However, the journey to process optimization within complex corporate organizations and systems can become daunting, often leading to stalled initiatives or unrealized benefits. Organizations must follow effective steps toward actionable process transformation to navigate this challenge and ensure optimal results.

This becomes especially crucial when integrating AI and automation into the optimization ambitions. While these technologies have the potential to streamline operations, their effectiveness hinges on thorough design and execution to prevent complications and inefficiencies along the way of implementing.

Core challenges of process optimization

Process optimization hurdles often stem from three primary causes.

Complexity: Processes traverse multiple departments and systems, each with unique priorities, requirements, and cultures. This complexity makes it challenging to determine where and how to start optimization efforts.

Lack of transparency: Complexity and silos can hinder data gathering and end-to-end analyses. This opacity extends to setting optimization goals, making it difficult to align them with strategic business objectives.

Subjectivity: Decision-making based on gut feelings and outdated analyses, coupled with varying stakeholder objectives, adds subjectivity to the optimization process.

A proven optimization strategy for maximum value

Drawing on extensive experience with large organizations, Capgemini Invent has developed a framework for navigating the challenges of complex process optimization journeys.

  • Set up for success: Invest upfront effort to understand what additional value for business stakeholders means from their perspective. Also, validate that this value aligns with your corporate strategy and objectives. Confirm the opportunity through outside-in benchmarking and choose to start with the business process domain that offers the most significant upside.
  • Let facts lead your way: Ensure that your root cause analysis goes beyond the obvious and surfaces tangible root causes of undesired business outcomes. Be pragmatic in how much you cover, but ensure you tie the findings back to the economic drivers you identified in the first phase. Finally, quantify the solution business case and agree on the path forward.
  • Realize and prove value early: Aim for quick wins that demonstrate you are initiating a value transformation while you continue driving the more challenging changes. Ensure that you use agreed metrics to track the outcome from the first day of value realization. Also, ensure additional stakeholders get engaged and educated along the way.
  • Build a pipeline: Build a dedicated team that embeds ongoing optimization into the company’s operation. Establish dedicated governance structures to drive and sustain business value through defined roles, work methodologies, tools, and decision architectures.

The above steps will get you started on your value journey. They can function as the blueprint for recurring and continuous business process optimization.

Guiding principles for your success

Capgemini Invent’s process optimization approach is built on guiding principles to ensure a successful and measurable realization of significant business value.

Selecting the correct problems to solve is paramount to a value-focused mindset. Understanding the potential outcomes of successful process improvement allows for better prioritization and analysis of use cases. This approach not only aids in justifying capacity allocation but also ensures that the organization recognizes the value of successful realization.

Setting the scope for process optimization projects wide enough to find enough value but small enough to complete in eight to 12 weeks is an art. The only prerequisites are access to accurate data, contributions from process owners and experts, and processes with substantial transactions and costs.

Starting with a stand-alone business process helps manage the complexity of your first endeavor. Aiming for a comprehensive end-to-end improvement spanning several business departments may be tempting. However, experience has shown that targeting the most costly or time-consuming processes within a department and looking at it stand-alone is sufficient to get started.

After initial successes, the challenge is to scale the approach enterprise-wide, making it a fundamental aspect of ongoing operations. Critical elements for achieving this include robust governance and funding mechanisms, a center of excellence, strategic technology stack selection, and a continuous focus on value realization and measurement.

Learn from the success of others

Here are some examples of the work we have done.

A global consumer products manufacturer has utilized process improvement to avoid food waste while decreasing cost. The client was faced with finished goods that stayed in its warehouses beyond the date at which they can be sold to end-clients. Data insights have revealed several root causes for that issue, including planning mishaps. We helped to avoid a share of the upstream drivers by using data to highlight when planned production is not in synch with the current demand for products. But also, downstream interventions have been defined. For products that are approaching their limit date, an AI component recommends the next best action amongst several options, like a stock transfer to another warehouse with a higher demand, a discounted selloff to a discounter with high demand for that product, or ultimately a donation to a food bank. The combination of these solutions has resolved most of the client’s food waste while also saving cost for food destruction.

A German retailer has improved the effectiveness of its supply chain planning process by using innovative technology and data insights. Initially, supply chain planners were using several diverse systems to pull information together on product demand, supply planning, and orders with vendors. This approach was making insight generation cumbersome and lengthy. Process mining technology allowed for consolidation of that information in one knowledge model that avoids the effort to pull information from diverse systems, but also assists in interpretation of the content. This allowed it to spot planning delays and supply risk in near-real time so planners can act accordingly and avoid impact.

A US-based pharmaceutical company was achieving significant growth but missed the opportunity to keep their business processes in synch. As a result, the company outgrew its business operations, leading to a decrease in the performance of the procurement and payables domains. Process engineering enabled the detection of the biggest process execution gaps and the quantification of the business opportunity from fixing those issues. The outcome was a prioritized roadmap for business improvement in the purchase-to-pay process with an annual savings potential of $35 million. Data insights also triggered the realization of this value by providing a detailed decomposition of which vendors and material groups are driving the issue’s majority. This deep insight enabled the respective process owners to conduct very targeted fixes.

Continuous improvement for long-term success

Once initiated, process optimization should become a continuous endeavor. This ensures that the organization continuously learns and adapts as processes improve, incorporating insights into future refinements. With a technology-agnostic and solution-oriented approach supported by impactful governance, organizations can cultivate a culture of continuous improvement, yielding increasing returns on effort over time.

Achieving maximum value through process optimization is not about a specific technology but rather about systematically evaluating processes, developing more intelligent workflows, and integrating technology where it adds measurable value in terms of efficiency and productivity.

Meet our experts

Thierry Kahane

Vice President in Capgemini Invent’s Enterprise Transformation unit | NA leader for the Process Engineering practice.
He brings a track record of more than 25 years of success across industries, building and leading teams in high-growth professional services and SaaS businesses, focused on advising senior executives in large complex organizations. He specializes in driving value through process engineering, digital transformation, innovation, and AI/ML and analytics solutions, and is recognized as an expert in accelerating execution and paths to value and as a trusted advisor in transforming client’s business and IT operating models by adopting innovative technologies. Thierry has also held multiple senior commercial roles in high-growth VC-backed start-ups offering high-ROI GenAI and AI SaaS solutions.

Jan-Malte Praedel

Director & Head of Process Engineering | Capgemini Invent
Connecting insights from business process analysis and process data mining, he helps organizations uncover, analyze, and solve business execution gaps. Jan-Malte brings over 15 years of experience in business process and IT consulting in North America and Europe across diverse sectors and process domains. He is specialized at helping organizations build the right programs, teams, and momentum to tackle business challenges in a data-driven way that overcomes resistance towards successful transformation.