As companies move to using more data to help them make better decisions, they are often left with an uncomfortable feeling. This feeling has nothing to do with going outside comfort zones or changing the way of working, it is based on the fact that even after using the data many people feel like their questions still aren’t answered properly.
And it is really common.
Research published in the Journal of Organizational Effectiveness People and Performance showed how more measurements, data and visualisation of HR processes lacked the ability to diagnose problems with business performance and lead to relevant and actionable insights. Our experience shows that this is not just limited to HR, it is across the whole business.
So why does this happen?
During COVID-19 (and even before it), supply chain companies around the world underwent significant digital transformations that led to the collection of more and varied data on all aspects of their businesses. To manage and understand this data, organisations invested heavily in BI tools such as Qlik, Tableau, PowerBI and more. Even though these tools are able to present good dashboards of the historic business operations, they haven’t produced revolutionary ways of doing business and, most importantly, they aren’t helping organisations deal with their most important challenge – the future.
From reactive to proactive
When businesses look at their dashboards full of data, they see patterns but are never 100% sure if they are real or not. In their historic data lies the answers to their future questions but how do we reveal them with confidence and precision?
Where BI provides you with the review view mirror, AI (artificial intelligence) provides you with a well calibrated telescope of the future. By using advanced analytics, companies are able to go from reactive to proactive by statistically validating intuitions about the future hidden in their data to give decision makers the confidence to place bold bets and target ambitious goals – a step change in the way of doing business. Often what the analytics discovers are things you “knew” but now you have quantified them and can properly compute the effects of your decisions on your bottom line.
Those sectors that stand to benefit most from using AI to go from reactive to proactive are those where there exists high variability in inputs and processes or demand for outputs. For example, industries which use inputs from nature such as mining, resources and agribusiness need to be able to deal with natural variation in their inputs. Any company selling into markets with volatile demand also needs ways to deal with this challenge.
And then there are a number of industries like logistics and agribusiness which face, and solve, volatility on both inputs and outputs.
How supply chains solve their predictive challenges
Biarri has worked with many logistics companies and agribusinesses to help them move from reactive to proactive. Instead of organisations harvesting crops or moving goods around trying their best to manage their volatility via inventory overcapacity, staff overtime and high wastage, they are now moving to scalable analytics with the business preemptively selling and optimising the expected yield from their crops, animals and delivery trucks.
A good example of this is Alliance Group in New Zealand who use Biarri’s supply and demand management tool Wolf, which has allowed them to better allocate supply to demand and smooth out their production cycles while simultaneously increasing their profit margins by selling more high margin products in niche markets in a scalable and low effort way. During COVID, this tool allowed them to quickly respond to changes in volatile global and local markets managing both high volatility on the input side (lamb sizes and grades) to the high volatility on the outputs side (COVID lockdowns drastically affecting demand).
In addition, moving to proactive can have other surprising benefits. Work Biarri has done with Australia’s largest grain exporters shows how a proactive view can reduce storage requirements, lower labour costs as well as save energy – let alone better serve their customers more confidently. Although not always the goal of predictive tools, the ancillary benefits can sometimes outweigh the initial business goals.
Why we all must do this
In moving to proactive thinking via advanced analytics companies are not only improving their bottom line and making better decisions, they are improving local and global markets. By smoothing out supply and demand, market volatility reduces and creates a better business environment for all. The benefits of this accrue to society via a better management of our resources leading to lower prices and higher living standards for all.
Moving from reactive to proactive via AI tools allows businesses to disrupt their current markets in a scalable way. Not only can you look around corners to know what is coming next, you can do it in a scalable way. Reach out to Biarri now to find out how.