In this article, I look at the concept of the Frictionless Enterprise and what it means for an organization’s finance function.
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Many organizations today operate in functional siloes that impact their ability to serve customers. Frontline functions such as sales, customer services, and marketing are wholly focused on the end customer, while enabling functions such as finance are accused of being too internally focused. Internal debates and process disconnects come at the price of customer experience, foresight, and competitive advantage. This is simply a byproduct of enterprise age and growth, while startups and platforms are often already established on a frictionless basis.
To compete, a frictionless enterprise must remove internal barriers and focus on market agility through redefined orchestration of processes from the front to back office. Our experiences show these frictionless enterprises enabled by well-integrated finance models deliver 30% improvement in time to market, 25% improvement in forecast accuracy, 25% sales growth in digital revenue streams, and 50% improvement in days sales outstanding.
As my colleague Lee Beardmore described in his article, a shift in the operating model that underpins the new Frictionless Enterprise is critical, and the finance function as a key protagonist of change given the frictions that exist today.
Addressing the friction in finance
Friction point 1 – it takes Finance 5–10 days of the next period and up to 90% of the effort to produce figures. This gives no time for the leadership to make fast decisions based on fact at moments that really matter.
Intelligence – is not a monthly ritual. The continuous close is a basis for equipping performance owners with fast, forward-looking, and freely available insight to execute the decisions that matter. These decisions affect how an enterprise captures customer, social, and environmental value, improves market competitiveness and resilience, while optimizing human and capital investment made in promotions and the supply chain.
Friction point 2 – qualified professionals are unable to do the job they were employed to do as they continue to swim in exceptions and poor experiences, impairing the customer experience to trade across billing, payment, fraud, and credit control.
Workforce – needs to be AI augmented with combination technologies that string together proprietary machine learning (ML) code, micro-apps, cloud ERP, and robotic process automation (RPA) to deliver more impactful outcomes than any finanace employee could deliver alone. Our Intelligent Orchestrator AI worker provides a frictionless experience in accounts receivable dispute handling with 10% human intervention. During the COVID lockdown, one of our clients was unable to staff their call center, which meant that their customers had no outlet to solve payment issues. We rapidly deployed a portal on the client website to flow queries directly to our AI worker, which then applied ML logic that enabled the appropriate next best action bot to respond 24/7. This created a frictionless experience at a time when cash was of the most concern to our client, improving customer retention and sales. Ultimately, the AI Orchestrator augmented the work delivered by a hundred humans.
Friction point 3 – over time, operating models have developed internal functional perimeters that help separate ownership, control, empires, ego, and sadly blame. This ultimately leads to energy being too internally oriented and not focused on the customer.
Proximity to customers – re-orchestrating processes, data, and experiences by removing the internal operating model silos between finance and supply chain functions. In turn these functions face off to commercial and local customer acquisition functions, ultimately bringing enterprises closer to their customers. In a world where customer demand has never been so dynamic, speed to market is a survival instinct enabled by the Frictionless Enterprise.
Friction point 4 – regulatory and financial controls cannot keep pace with the agility of shifting business models and dynamism in the market. For example, the trend of B2B enterprises launching B2C propositions overnight, leaves a swathe of controls needing to catch up. Internal audit teams often have no prior experience or sufficient time to embed the right controls given new risks in local tax and banking jurisdictions, data privacy, and or payment processing regulations. As humans cannot control every risk, they must accept risk and prioritize based on history, judgment, materiality, and the available resources.
Controls – even the most established control frameworks are still let down by the friction of human interpretation on historic data. Embedding core SOX and regulatory controls into day-to-day processes eliminates the risk at source. Introducing the AI worker in the controls space brings the dynamism of machine learning and statistical techniques to determine the optimum threshold for automation-based intervention of vast data sets and reduce the risk corridor to negligible values. One example is in the materiality thresholds applied to foreign currency transaction posting and translation. We have identified cases where P&L exposure below stated materiality is significant month on month (millions of pounds), which an AI worker would refuse to accept.
Friction point 5 – technology in Finance continues to be process-oriented and internal, with limited uptake of exchanging data or permissions in an open source format with other enterprises. EDI and network platforms are still largely unsaturated due to cost of adoption, compatibility or security. For a simple B2B sale to be made internationally, we have seen over 20 pairs of hands touching a transaction across the lifecycle before cash settlement and anywhere between 50–100 key data fields being transmitted. The magnitude of a single human keystroke error will snowball friction in both organizations.
Technology – technology in finance continues to be process-oriented and internal, with limited uptake of exchanging data or permissions in an open source format with other enterprises. EDI and network platforms are still largely unsaturated due to cost of adoption, compatibility or security. We are starting to address gaps in large single platform models by inter-operability of small tech and big tech in smart ecosystems.
Investing in the future
Developing this frictionless finance environment needs a blueprint and framework built on experience. Our Finance Powered by Intelligent Automation (FPIA) team leverage Capgemini’s Digital Global Enterprise Model (D-GEM) platform to deliver frictionless outcomes to our clients. D-GEM provides a complete overview of an organization’s people, processes, technology, and governance with control points, accelerating the transition to transformed, future-proof processes. For finance, it includes next-generation AI-enabled O2C, P2P, record-to-act (R2A), and analytics.
Creating a frictionless digital ecosystem means continually seeking out new technology interventions and partnerships to increase business outcomes available from automation, embedded AI, and analytics.
The future is frictionless
Together with our clients, we are pushing the boundaries of frictionless and investing in our D-GEM platform to re-orchestrate the enterprise business processes, talent profile, and augmentation of AI with humans, driving outcomes that reach the customer’s customer. By making it simple for our clients to trade and function, we build momentum of frictionless that becomes the norm.
That’s certainly the direction of travel here at Capgemini – and it’s shaping up to be an exciting and rewarding journey.
Brijesh Patel helps organizations reduce friction across the enterprise – having worked in digital, customer experience, supply chain, and finance – to introduce more agile operating models augmented with AI to drive sizable business outcomes from transformation.