Digital Performance Improvement

Digital performance improvement under time and results pressure follows a different logic from proactive efficiency programmes. The goal is not a carefully planned transformation, but measurable results improvement within a defined, short period – with each measure legitimised in advance by a business case and its impact measured continuously. AI thereby accelerates both the identification of the most effective levers and their operational implementation.

Context and relevance

Companies in an earnings crisis face a fundamental dilemma: the situation requires rapid action, but every misallocation of resources or wrongly prioritised measure worsens the starting position further. Classic performance-improvement approaches – structured analysis, concept development, implementation planning – are geared to a timeline that is not available in a crisis context.

The overarching goal of every performance-improvement programme is the maximisation of return on equity. The DuPont equation makes clear where the three levers lie: profitability can be maximised through revenue growth and cost reduction, operational efficiency through the reduction of tied-up assets, and financial leverage through active equity management. As Figure 1 shows, concrete measures can be derived along these three dimensions – from digitalisation and e-commerce through lean processes and automation to working-capital optimisation and inventory reduction. AI changes the speed with which these levers can be identified and quantified. What classically takes weeks, such as the analysis of cost drivers, the prioritisation of revenue levers and the assessment of asset efficiency, can be compressed into days through AI-supported data evaluation.

Figure 1: Increasing return on equity – fields of measures along profitability, operational efficiency and financial leverage (DuPont equation)

Our approach

FOSTEC & Company’s approach operationalises the DuPont lever structure along three impact dimensions – as shown in Figure 2. All three dimensions are amplified by AI and implemented by high-performance teams with a clear results mandate. The goal is the AI-driven reallocation of resources: automation reduces operational effort and shifts capacities into growth-relevant functions.

Pillar 1: AI-supported process automation

AI-based automation identifies and eliminates manual activities faster and more precisely than classic lean analyses. Freed-up capacities are redirected immediately into results-relevant tasks. Typical measures:

• AI-supported analysis of the process landscape and automatic identification of automation potential by impact and feasibility
• Automation of repetitive administrative and operational processes – from invoice processing through reporting to inventory management
• AI-based anomaly detection in cost and process data for continuous efficiency management
• Reallocation of freed-up capacities into sales, customer service and commerce growth

Pillar 2: AI-enabled high-performance teams

High-performance teams implement with a direct results mandate – supported by AI-supported decision-making that accelerates data evaluation and option assessment. Typical measures:

• Build-up of interdisciplinary teams with clear results responsibilities and short decision paths
• AI-supported real-time monitoring of implementation progress and impact per initiative
• Agile implementation cycles with weekly progress reporting towards management and investors
• AI-based prioritisation tools support teams in resource allocation under time pressure

Pillar 3: AI-driven commercial excellence

AI-supported management of pricing, demand and customer experience unlocks revenue potential that cannot be identified under time pressure without data-based support. Typical measures:

• AI-based pricing intelligence: dynamic price adjustment based on demand, competitive and margin data
• Data-driven channel management: identification of the most profitable sales channels and reallocation of marketing budget
• Hyper-personalised customer experience through AI-supported targeting and offer optimisation
• Real-time insights for marketing and sales: AI models identify revenue levers in ongoing campaigns

Figure 2: Performance-improvement framework – AI-supported process automation, AI-enabled high-performance teams and AI-driven commercial excellence as three impact dimensions

The three pillars act as an integrated programme: AI-supported process automation frees up operational capacities and shifts them into growth-relevant functions. Results-oriented implementation teams translate the analysis results into operational measures within a direct scope of responsibility. AI-supported pricing and sales management unlocks revenue potential that could not be identified under time pressure without a data basis. Implementation follows three steps: an AI-supported initial analysis across all RoE dimensions with a prioritised list of measures, a business-case development per initiative with ongoing progress tracking, and a results-oriented implementation with real-time impact monitoring as a basis for management and communication towards management and investors.

Results and impact

Digital performance improvement under results pressure generates impact on two levels simultaneously: immediate P&L improvement through prioritised measures with an underlying business case – and structural results improvement through the interplay of the three impact dimensions, which together achieve more than the sum of their individual measures. Process automation frees up capacities that are redirected into growth-relevant functions. AI-supported pricing and sales management unlocks revenue potential that could not be identified under time pressure without a data basis. The impact monitoring makes P&L effects per initiative visible in real time – as an operational basis for management and as a robust basis for communication towards investors and banks. The difference from classic performance programmes lies in the combination of analysis speed and operational commitment: AI compresses the diagnosis into days instead of weeks, each measure is legitimised in advance by a business case, and impact measurement begins immediately with implementation. This shortens the time between problem identification and the first measurable results improvement and creates the transparency that is required towards all relevant stakeholders in restructuring situations.

Position within the service portfolio

The Turnaround & Restructuring portfolio brings together the central levers for stabilising, restructuring and repositioning companies in critical situations. Optimisation takes place along clearly defined fields of action:

• Commerce & Digital Performance Diagnostic
• Rapid Profit & Margin Recovery
• AI-Accelerated Turnaround & Performance
• Commerce & Channel Restructuring
• Crisis Operating Model & Structural Cost Reset
• Stakeholder & Investor Communication
• Value Creation & Exit Recovery

Find out in a personal introductory conversation how FOSTEC & Company identifies and implements digital performance improvements in your company under time and results pressure – get in touch with us.