Artificial Intelligence (AI) has firmly taken root in our everyday lives and in many instances, such as the smart speakers we find in our homes, this AI is apparent and relatively simple.
But when you use that same speaker to make an online purchase, you may be less aware of the complex AI that is involved in the process of picking and packing that item in a warehouse and routing it for delivery to your doorstep.
The world of business is full of similar use cases for complex AI, where the technology is transforming business performance. However, something that underpins all of these processes is the need for planning. For example, how did the aforementioned supplier know what the demand for their product was going to be in the first instance? This is where ‘intelligent planning’ – the application of AI to business forecasting and planning processes – comes in; another example of complex AI. Traditional planning techniques would have involved historic trend analysis and human judgement, but with intelligent planning, the supplier could have exploited much more advanced predictive analytics.
Intelligent planning provides the opportunity to consume, exploit and create actions based upon much larger volumes of data and identify patterns within it that would otherwise be impossible. It can also remove the bias inherent in rules which have been defined and coded by humans. Based on the data it is fed, intelligent planning can then be used by organisations to automate, predict and prescribe the right course of action for any business process, from forecasting and scoring, to optimisation and categorisation.
But implementing any kind of AI technology isn’t a straightforward process and there are a number of considerations to take into account beforehand.
Understanding the opportunity for intelligent planning
Compared to current planning activities, which invariably work on pre-defined cycles such as weekly or monthly processes, intelligent planning can be considered to have more of an ‘always-on’ approach. Large volumes of unstructured data can be analysed in real-time to identify patterns that can be used to make decisions or simply recommend the appropriate course of action. As such, any business that has access to data that exceeds the volume that humans can analyse and understand, will need intelligent planning to remain competitive.
For example, a large retail organisation can harvest data from millions of daily transactions to make better buying, customer engagement, and operational decisions. But they don’t need to stop at short-term future actions; instead they should consider using social media sentiment and detailed demographics to make longer term, strategic decisions around areas such as range, store locations and customer experience.
Financial services is another prime candidate for intelligent planning, particularly where understanding and influencing consumer behaviour is involved, for anything from calculating the probability of a customer renewing their insurance policy; the likelihood of a loan holder defaulting on their payments; or the future spending profile of credit card customers.
Intelligent planning will enable these types of businesses to produce increasingly accurate forecasts and allow them to apply more lateral thinking to the planning process.
Approaching planning in a strategic manner
With the opportunity for implementing intelligent planning being significant and broad, there is a risk that businesses could approach it in a ‘gung-ho’ fashion. Worse still, they could fall into the trap of looking for problems for a new solution to solve, even where those problems don’t exist. Businesses need to wait for the normal business challenges or opportunities for automation to naturally bubble to the surface, but when they do, they shouldn’t be tackled on a piecemeal basis.
Implementing intelligent technology can involve significant investment for companies of any size, so it’s important to approach it in a considered manner. Businesses, along with their IT and data experts, are still finding their feet when it comes to approaching and implementing AI technology. They lack the experience born out of decades of more mainstream technology enabled change implementations. So, to try and overcome these challenges, the obvious approach to adopt is to pilot intelligent planning solutions in the first instance and if it comes to it, fail-fast.
Ensuring senior buy-in from the beginning
Smart business leaders start with a vision for AI and an up-front understanding of what it can do for the business. Given the potentially wide reaching impact of intelligent planning, the fact that it typically won’t sit in functional silos, that it is still extremely novel and that it can be hugely disruptive to any business, the decision can ultimately only come from the top. The C-suite therefore plays a huge role in sponsoring the introduction of the technology.
For these same reasons though, management can be hesitant to make any final decisions without having access to concrete evidence that proves it is worth the investment. But as the technology is still in development and emerging, this kind of evidence is next to non-existent. Added to this a gap in understanding of the technology that has only recently started to be filled, and people are only just beginning to appreciate AI as a real-life solution, as opposed to something from a sci-fi film.
Eventually, AI technology will become a more mainstream solution, but in the meantime, companies are going to come across an abundance of challenges to tackle before any solution can be implemented successfully. What’s more, it’s far too big a leap to take at once, so businesses need to make the transition to intelligent planning in stages. And on the journey from traditional siloed planning through to intelligent planning sits Connected Planning.
Connected Planning entails joining up planning activities across all business functions so that forward looking decisions ripple through the entire organisation, allowing the full impact of any single decision to be assessed holistically. Over the course of time, intelligent planning can and will be woven into a businesses Connected Planning ecosystem.
About the Author
Adam Bimson, Director and Co-founder, Vuealta. Adam has over 15 years experience in Performance Management and Business Intelligence and has delivered successful change into a wide range of clients including FTSE 100 organisations, international assignments and public sector bodies. He has experience of many sectors, with his current focus including Insurance and Consumer Goods, both of which have high demand for planning and modelling capabilities.
Featured image: ©Siarhei