The future is here. Are you ready?
- Mohit Malhotra
- Apr 22, 2024
- 5 min read
The world of tomorrow is approaching us faster than anyone can predict – and in some cases, it’s already here. Companies are already moving towards voice-activated business software. Emerging technologies like artificial intelligence, machine learning, blockchain and IoT are driving new business models that nobody had ever heard of just a few years ago. Data can be harnessed for everything from designing shoes to hiring your next superstar. Every organization needs to ask itself: are we ready for this future?
The digital divide is widening
Today’s best performing companies have almost twice more economic profits than 20 years ago
You might ask yourself, “Why is it important to change now? We’ve been operating on the same business model for 20 years, and we’re doing okay.” But according to research over the past 20 years, what’s known as “best-performing” companies are taking an even more significant share of the market away from average organizations. Today’s superstar firms have almost twice more economic profit on average than they did 20 years ago. Meanwhile, the bottom-decile firms have 1.5 times more economic loss on average than their counterparts 20 years ago. These digital best-performing companies are redefining what success looks like today, and the widening of this gap can be attributed to the use of emerging technologies.
4 ways to analyze business dynamics:
1. Consumer-Centric Growth: Consumers have unprecedented power & information at their digital fingertips, with ever-increasing expectations to go with them. This shift in expectations now requires more investment for mass-personalization, customer service and frictionless commerce. New players are reinventing traditional models with outside-in thinking and entirely new ways to serve.
2. Digital Relevancy: Digital capabilities include delivering 1:1 personalization, scalability & distributed manufacturing. Linking the connected consumer, home, product & store with the supply chain in real-time and responding to changing consumer needs through technology innovation. Digital consumers now expect on-demand and service-based models.
3. Value Chain Collaboration: Demand-driven digital value chain
4. Innovation at Speed: Adaptive cultures, processes and technologies
Is your back office holding you back?
According to research, over 90% of people would trust orders from a robot? Surprised? Most are. Emerging technologies are impacting business, and people are acclimating to it faster than we think.
Technology is changing how people interact with machines and how businesses are using it to improve performance; it is causing unprecedented disruption. Enterprises are forced to rethink their business as the evolving market is changing how customers interact with products, how employees perceive their work and how competitors are innovating
3 Ways to be future-ready & outpace change:
1.Optimize business operations: Driving process automation at scale, re-engineering legacy business processes, and keeping a “digital-first, cloud-first” mindset
A unified cloud helps businesses be future-ready and outpace change
Respond to disruption
Establish continuous close
Manage seasonal business
Accelerate speed-to-decision
Improve operational efficiency
It can recommend what to do next, and it learns from business responses so that it can automate those tasks in the future.
SMART innovation answers the following questions:
Knows who you are?
What you need to know?
What you need to do next?
Where you need to go?
Areas for possible automation
Pre-populated workflows
Touchless transactions
Improved user experience
Recommended actions
Policy and compliance
Anomalies and fraud
Continuous close
Optimized working capital
Increased strategic focus
2. Outperform with intelligence: Connecting data enterprise-wide, using AI to uncover hidden patterns, and gaining insight to make better business decisions
Connect data to generate new insights
Machine learning works best on large sets of data – typically much larger than your own internal data. Using large pools of 3rd party data, you can find correlations and drive better predictions.
For example:
1. What if you could improve forecast accuracy by better highlighting foreign currency risk in consolidated forecasts?
2. What if you could use machine learning on SEC XBRL data to highlight micro or macroeconomic trends that might impact a single customer?
3. You can leverage certain leading and lagging indicators such as housing starts, CPI/PPI, or even historical rainfall to better train algorithms.
4. And you could monitor transactions in your ERP or operational systems to notify you of material invoices that might require an adjustment to the forecast.
What’s required? Faster analysis to action
Signal detection
Root cause analysis
Insight discovery
Action recommendation
Collaborative reporting
Yesterday: If you look at traditional efforts to understand and analyze enterprise performance, the vast majority of time and effort went into gathering and manipulating and reconciling the data. Think of the hours or even days you’ve probably spend trying to consolidate Excel spreadsheets – we’ve all been there.
Today: The goal is to spend less time on LOW-VALUE tasks (like data manipulation and reconciliations) and more time on HIGH-VALUE tasks (like data analysis). However, the lead time between ‘analysis’ and ‘action’ is still too long. Most organizations still feel like they don’t have enough time to engage with the operations.
Tomorrow: The future of enterprise performance management can take organizations so much further. By dramatically improving the “data analysis” stage, it allows more time for finance to engage with operations and arms them with better data. The goal is to MOVE FROM ANALYSIS TO ACTION much faster and with better insight than humans could not easily find on their own.
To accomplish this, automate steps that can be done faster by a machine as compared to a human (such as pattern recognition). Provide insights that a human would have difficulty uncovering within a reasonable amount of time through machine learning and AI. For example:
Find budget/forecast variances by product, by entity, by market, by geo, etc….
Find troubling trends in historical data
Find troubling trends in ‘predicted Actuals’ data (e.g. manually run predictions for data coordinates, then look for potential issues).
Find data omissions (e.g. headcount data existed in entity ABC last period, but does not exist this period)
Machine learning & AI can also find correlations in the data that humans can’t easily spot, such as:
Correlating driver data & account data
Correlating data in financial plans with data in operational plans (e.g. revenue is down for product ABC, which correlates to a recent staffing shortage in the call center for products ABC)
Finding root cause analysis
Overcoming bias in numbers (e.g. EMEA historically under-estimates forecasted revenue by 5%, NA over-estimates by 15%)
Organization goal is to give finance and operations teams more time to ‘take action’ by spending less time in analysis.
3. Exceed customer expectations: Delivering better business outcomes and exceeding customer and employee expectations
So what’s the final thing that digital leaders do well? With cloud and AI and machine learning and all these new, predictive technologies, they’re delivering better business outcomes and exceeding customer expectations.
When you connect back-office excellence to front-office sales and service, you get a better customer experience – a one-company experience without silos.
With a unified solution for the entire enterprise together in a shared cloud is the complete solution. It provides an end-to-end business operating model so you can break down organization and data siloes, gain efficiency and improve productivity.
From emerging technologies such as machine learning and artificial intelligence to automated processes and predictive analysis, you get easy access to actionable insights to increase efficiency and drive innovation. And it’s infinitely adaptable to the changing needs of your enterprise. You can unshackle your teams from the rigid, often outdated processes of your old systems and give them a system that can change, expand and adapt as needed.
And finally, the value of now…
Research suggests customers have realized a broad range of benefits in
1. Operational efficiency: productivity gains, reporting productivity
2. Finance modernization: closing process
3. Business agility: Reduction in time-to-market, Reduction in decision-support costs, Drop-in maintenance costs, Decrease in planning and performance costs
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