In recent years we’ve seen an acceleration in the adoption of emerging technologies as consumers have come to realize the value capabilities like robotics, artificial intelligence (AI), and machine learning (ML) can provide. Ana Pinczuk, chief development officer, Anaplan, demystifies AI and ML-based forecasting for effective implementation.
While these technologies have arguably become more mainstream, skeptics still exist. Questions around the elimination of jobs, trust, and bias are still top of mind – and for some, a general fear of the dystopian outcomes often seen in sci-fi films can be all-consuming.
But the positive impact emerging technologies – especially AI and ML – can have in a complex, fast-moving, and volatile business landscape cannot be overlooked. That’s why it’s critical for technology leaders to help demystify these capabilities and the role they can play so that organizations feel comfortable, and confident, harnessing the power of AI and ML to plan, react, and compete successfully in today’s dynamic market.
Agile Businesses Need Agile ProcessesÂ
Let’s start with a single, yet powerful application – forecasting.Â
Every team, across every department, relies on forecasts in some way, shape or form. Finance teams generate revenue forecasts to help executives maximize profit and deliver shareholder value; HR teams forecast headcount needs; supply chain leaders forecast demand to optimize inventory, and marketing teams leverage forecasts to allocate promotional spending.Â
Regardless of the department, the traditional forecasting process looks the same: a lengthy, often manual exercise, where teams try to glean insights from typically small slices of data – or a large stack of Excel files. This is not at all conducive to the agile, on-the-fly decision-making required in today’s fast-paced business environment. Just think of the effort it would have taken to manually re-forecast production levels each time a new factory or warehouse had to close in early 2020 because of the pandemic.Â
Making Accurate Forecasts AccessibleÂ
This is where the value of AI and ML comes into play.Â
When companies start leveraging AI and ML to enhance their forecasting capabilities, they can tap into more data than ever before, all in real-time, to ensure their forecasts reflect both the current environment and the needs of the organization. This includes historical data, business metrics, and external factors – like weather data. At the same time, deep learning algorithms can automatically evaluate and test multiple scenarios and find correlations between those scenarios to pinpoint emerging trends. Based on these insights, the algorithms can automatically select the best predictive model for each unique business use case to ensure the resulting forecasts are more accurate – and more useful than ever before.Â
Another win for today’s businesses? AI and ML-based forecasting make advanced intelligence accessible to all business users – not just data scientists. This means you can extrapolate helpful data and insights, view potential outcomes, and get recommendations on how to proceed without having to rely on IT teams or technical support. This is crucial as it democratizes the benefits that each employee, team and process can unlock from these merging technologies.
Say your company needed to fine-tune your demand forecast for the next two quarters in response to rising inflation and slowing consumer spending. AI-and-ML-based forecasting could help you leverage internal data, like historical demand and SKU data, and external signals, such as market volatility or consumer shopping trends, to predict demand for tens of thousands of SKUs and model multiple commercial pricing and promotion scenarios to help you strategically shape that demand in the coming months.Â
See More: Top 10 AI Development and Implementation Challenges
Debunking MisconceptionsÂ
The positive impact AI and ML can have on a traditional business process like forecasting is clear, so why are some business leaders still hesitant to adopt emerging technologies? Common misconceptions around cost and complexity might be the culprit.Â
While they might be open to exploring the use of emerging technologies, many business leaders equate these technologies and applications with high price tags. It is true that some emerging technologies are still cost-prohibitive, but the emphasis we see in the market today around ecosystem partnerships and integrations is changing that narrative. And, with the rise of cloud marketplaces, AI-and ML-based business applications are more cost-effective than ever before. Even with initial investments that may seem a little steep, especially for SMEs, most enterprises ultimately reap the benefits manifold.
The same can be said for misconceptions around complexity. In a competitive market, leaders do not want to invest valuable time and resources into configuring, deploying, and maintaining intelligence systems. Thankfully, the proliferation of data and the rise of low-codeOpens a new window and no-code platforms and solutions has democratized access to emerging technologies for all business users. This is a game-changer for businesses because it allows internal teams – from finance to HR – to get the most out of intelligence capabilities without needing any prior coding, IT or data science experience.Â
Embracing IntelligenceÂ
The transformative power of emerging technologies is here. And while we still have much to learn, it’s clear that intelligence capabilities like AI and ML can have a positive impact on business operations, especially in a dynamic, fast-paced environment. With every emerging technology, there is often a collective learning curve. organizations need to start making AI and ML a lot more accessible and friendly. Only then, with greater participation, will their true potential be realized.
Advanced, artificial intelligence solutions are quickly becoming an essential aspect of our daily lives – at work and otherwise. Adaptability and scalability are joint pillars that serve as foundations for the evolution of these tech solutions. Users and organizations, therefore, need to be educated in the efficient use of these technologies. Debunking misconceptions is a good place to start when it comes to building a culture of learning, agility and growth.
We might not be able to debunk every myth or misconception, but if we start with a specific application, like forecasting, we can help businesses reframe the way they look at these capabilities. The change in the narrative – from complex, costly, and dystopian to dynamic, accessible, and impactful –will help business leaders transform hesitation into excitement.
Tech advancements are often met with resistance and even fear, but that usually gives way to a deeper understanding of how they enable processes and lead to our ease of use. It will no doubt take time, but eventually, leaders will be well-positioned to truly take advantage of these technological advancements as they look to drive a new era of growth, value, and competitive edge for their organizations. Â
What are the most significant benefits of AI and ML for your business? Share with us on LinkedInOpens a new window , TwitterOpens a new window , or FacebookOpens a new window . We’d love to know!