Category: healthcare-pharma

Pharmaceutical How Scout Assisted Bayer Navigate a Complex SAP S/4HANA Migration Watch video The Customer Bayer, a leading pharmaceutical company with over 110,000 global employees and an annual revenue of approximately $40 billion faced a significant challenge: migrating their complex SAP ECC systems to SAP S/4HANA as part of their CORE transformation program. This multi-year initiative aimed to streamline business processes across their global operations in the EMEA region. Industry Pharmaceutical Location EMEA 110,000+ Employees ~$40B Annual Revenue 110,000+ Employees ~$40B Annual Revenue The Challenge Massive Scaleand Complexity The multi-year S/4HANA migration required careful coordination and detailed planning across a vast array of processes and applications. Risk of Errors There was a substantial risk of errors during the fit-to-template analysis, which could lead to critical process failures. Undocumented Process Variations Variations in the as-is processes across core and satellite applications were undocumented, further complicating the migration effort.Scout’s expertise was crucial in overcoming these challenges, ensuring a smooth and efficient migration while significantly reducing manual effort for Bayer’s Customer Interaction (CI) team. Enter Within 4 weeks of deployment, Scout mapped 3600 hours’ worth effort across 18 users in Bayer’s Customer Interaction, Supply Chain and Master Data Management teams. Scout also began identifying redundant effort, validating benefits from Bayer’s CORE implementation. Within just 4 weeks of deployment Scout mapped 3600 hours’ worth effort The Pre-Migration Deployment of Scout To address these challenges, Scout was deployed to aid discovery analysis and facilitate a smooth transition. The deployment focused on: Business and Leadership Teams Gaining comprehensive visibility into all processes and understanding how work is executed. Identifying short-term improvements to processes ahead of the S/4HANA migration. Mapping interactions between SAP and other applications to ensure seamless integration. CORE Team Providing detailed insights into how SAP is utilized within processes. Offering data on usage at a module/T-code level to help test the viability of the future-state process. The Pilot Scout was initially deployed in Bayer’s supply chain teams in Spain, Portugal, and potentially Switzerland, which were pilot countries for the CORE implementation. The goal was to drive data-driven decisions to ensure the migration’s success and foster wider continuous improvement efforts. Scout’s AI to “find and fix” Step 1: Find Scout provided detailed insights into current processes by scouting 43 and identifying 73 variations, potentially discovering 19 non-core applications. Scout also identified and highlighted areas where manual checks were being performed, pinpointing specific processes that could be automated. With AI layered on interaction data, Scout offered comprehensive and consumable visibility across core and satellite applications. Harvard Business Review Do You Know How Your Teams Get Work Done? Read more Step 2: Fix By implementing the insights provided by Scout Bayer was able to: Eliminate manual checks, saving the CI team 430 hours of effort De-risk the CORE pilot with a significantly lower cost to program. Significantly minimize integration efforts. It is important to note that in all of these recommendations, privacy was of the utmost importance – and no employee data was shared. Empathy was at the core of all recommendations and the focus was on addressing and improving the core issues i.e. Getting teams to work together across functions Fixing disconnected systems Simplifying and optimizing work processes Business outcomes In summary, Scout was able to drive the following business outcomes Eliminated manual checks to save 430 hours of effort Help de-risk the CORE implementation pilot Lowered cost to program AI connects interaction data to business outcomes Scout lights up the ‘dark side of the moon’. Your business generates billions of data points from team-machine interactions. Scout, our AI model, deciphers this interaction data to reveal what often remains unseen—the hidden challenges your teams face at work and how they affect business outcomes, whether it’s cost optimization, revenue growth, customer or employee experience, or business continuity. The AI then provides data-based recommendations to address these challenges, paving the way for improved outcomes. Forbes The ‘Dark Side Of The Moon’ In Enterprises Read more

How Bayer reduced cost of operation by 30% through post-merger transformation using AI Bayer, a global 500 pharmaceutical company grappled with post-merger challenges, striving to achieve synergy targets, particularly in streamlining supply chain operations. The delay in realizing critical assumptions increased pressure on the CFO and management to fulfill commitments made to the board. Scout to “find and fix” Scout’s AI model was quickly put into action across, 7 teams in 12 countries. The AI analyzed how supply chain teams interact with various applications, mapping out how and why work happens the way it does within the supply chain operations which led to: 30% Reduction in Operational Costs: Streamlining processes and reducing inefficiencies. 10% Improvement in Cash Flows: Reflecting a more efficient and reliable supply chain process. 25% Reduction in Delays and Errors: In order processing, enhancing reliability and customer satisfaction Summary Join us to explore Bayer’s transformative journey with Scout insights and discover how leveraging technology can drive operational efficiency and strategic alignment in your organization. Watch Radovan Simic, Bayer’s Head of Digital Transformation, as he explains how Bayer improved its planning processes using Scout insights. Scout identified inefficiencies, showing too much time was spent on manual tasks in MS Excel instead of the ERP system. These insights led to streamlined processes, boosting productivity and employee satisfaction. Looking forward, Bayer plans to use Scout insights for their SAP S4/Hana implementation, aiming to streamline operations and prepare for future upgrades. Bayer’s experience with Scout shows the importance of continuous improvement, bridging the gap between human skills and AI, and fostering a culture of innovation. Watch how Bayer’s use of AI and Interaction Data helped their organization’s operational efficiency and strategic alignment. Explore more Transformation Stories https://www.youtube.com/watch?v=jrSRokN1WAoMorgan Sindall reverses reputational risk with Scouthttps://www.youtube.com/watch?v=fgXjjFaPB2oTransforming customer & employee experience at LNER with Scout Industry recognition Everest Group Leader in PEAK Matrix® Assessment: Digital Interaction Intelligence, 2024 NelsonHall Leader in NEAT Assessment: Process Understanding, 2024  HFS Research Enterprise Innovator in HFS Horizons: Process Intelligence Products, 2023  Forrester Strong Performer in The Forrester Wave™: Process Intelligence Software, Q3 2023  Soroco rated 4.9/5 in Gartner Peer Insights by our customers.  5/5

Pharmaceutical A Global Pharma Company Reduced Operational Costs by 30% through Post-Merger Transformation with Scout Email it to me The Challenge A Global 500 pharmaceutical company was struggling with the aftermath of a significant merger and acquisition. The management faced the daunting task of realizing synergy targets committed to the board, particularly in consolidating processes, teams, and systems within the supply chain operations. These critical assumptions had yet to materialize, putting the CFO and the entire management under pressure to deliver on their promises. Industry Pharmaceutical Location Global Attempted Solution before Scout Demanding 12,000- 15,000 hours of business users involvement was unsustainable The CFO, Head of Supply Chain, and Chief Digital Officer, along with their internal digital transformation team and system integrator, embarked on a mission to rectify the post-merger challenges. They deployed a process mining solution and organized manual ‘discovery workshops’ to understand the work patterns of their teams. However, these methods proved to be time-consuming and inadequate, demanding an unsustainable 12,000-15,000 hours of business user involvement across 66 processes and 13 countries, without providing the insights needed. Enter The CFO and Chief Digital Officer then evaluated and onboarded Scout to find and fix these problems. Scout’s AI model could be quickly put into action because it didn’t need complicated integration with current systems. The AI analyzed how supply chain teams interact with various applications, mapping out how and why work happens the way it does within the supply chain operations. This led Scout to discover a key insight: the root of the problem was not just within the supply chain teams but due to poor visibility of key process information and lack of clear SOPs. Scout’s AI model could be quickly put into action across 5 clusters in 13 countries, because it didn’t need complicated integration with current systems. Scout to “find and fix” Step 1: Find As the first step, the AI decoded the work patterns of the supply chain teams and connected them to business activities, simply by analyzing interactions between the teams and their software. It then automatically classified these work patterns as either core or non-core supply chain operational activities. Based on this analysis, within two weeks, Scout’s AI model provided the following insights: Contrary to popular belief, only 58% of the team’s effort was spent on core supply chain applications and activities. This surprising statistic pointed to a significant work recall gap across the team, highlighting the disparity between the team’s understanding of how work is being done and how work was actually being done. Harvard Business Review Do You Know How Your Teams Get Work Done? Read more The AI also determined that the remaining 42% of the time was spent manually managing multiple spreadsheets, organizing and feeding data into various supply chain systems, addressing queries and coordinating with regional and central supply chain teams and suppliers on communication apps. It also pointed out regional discrepancies, like teams in Southeast Asia spent an average 30% of their time on order management in Excel spreadsheets whereas the teams in India, Bangladesh and Sri Lanka spent 70% of their time on Excel spreadsheets. Scout’s AI model further uncovered operators 1200 context switches per operator per day, due to toggling between applications due to information silos and disconnected systems. These bottlenecks were forcing the team to incessantly toggle between different applications, ultimately resulting in a significant loss of productivity. Harvard Business Review How Much Time Does Having Too Many Apps Really Waste? Read more Harvard Business Review What’s Lost When Data Systems Don’t Communicate Read article Step 2: Fix Based on the above insights, Scout’s AI model recommended two levels of fixes: Quick Fixes These were ‘no-code’ fixes based on standardization and user training Deep Fixes Systemic and long-term fixes planned across the organization It is important to note that in all of these recommendations, privacy was of the utmost importance – and no employee data was shared. Empathy was at the core of all recommendations and the focus was on addressing and improving the core issues i.e. Getting teams to work together across functions Fixing disconnected systems Simplifying and optimizing work processes Business outcomes The strategic implementation of Scout’s recommendations led to: 30% Reduction in Operational Costs: Streamlining processes and reducing inefficiencies. 10% Improvement in Cash Flows: Reflecting a more efficient and reliable supply chain process. 25% Reduction in Delays and Errors: In order processing, enhancing reliability and customer satisfaction. AI connects interaction data to business outcomes Scout lights up the ‘dark side of the moon’. Your business generates billions of data points from team-machine interactions. Scout, our AI model, deciphers this interaction data to reveal what often remains unseen—the hidden challenges your teams face at work and how they affect business outcomes, whether it’s cost optimization, revenue growth, customer or employee experience, or business continuity. The AI then provides data-based recommendations to address these challenges, paving the way for improved outcomes. Forbes The ‘Dark Side Of The Moon’ In Enterprises Read more Download this customer success story Enter Business Email ID