Prescriptive analytics can cut through correlating and causal performance drivers when linked to a solution that is fit for purpose for each situation. This enables a laser focus on key areas where behavioural modification is needed so that automation can drive substantially increased efficiency.
A growing trend of implementing prescriptive analytics for improved performance in operations are Virtual Experts – recommendation tools for operators prescribing optimised set points to manage contextual process variability in real time. These tools enable substantial uplift in process yield, throughput, quality, cost and emissions.
Delivering the ‘proof of value’
Building simple integration between operator and data scientists
Getting the analytics model right is only 25% of the solution
Many organisations work with their data scientist and/or outside firms to develop predictive analytics, but they often do not make them practical enough or actionable at the frontline. As they embark on these macro change programs, they tend to fall short on adoption by the frontline and typically do not deliver the expected value.
At a foundational level, this is because there is a primary focus on tools & technologies and having ‘perfect’ data rather than driving operational improvement outcomes.
Ours is a proven strategy for how to go from reactive to predictive and from predictive to prescriptive. It centres on a simple pilot that demonstrates ‘proof of value’ before making substantial investment.
Proof of value informs a carefully designed, phased and short‑term gated approach to ensure hard dollars are not wasted on initiatives that provide little value. It focuses on value drivers and levers that will provide positive outcomes: What have we learned from the data? What are the insights? How can they be applied today? What must operators at the front line change or be able to do? What is missing? What uplift is achievable if a Virtual Expert is implemented?
Unlocking the value of prescriptive analytics tells an organisation when something happens, why and what they should do to correct for it – providing operational recommendations that are fit for purpose and drive accelerated outcomes. Operations teams will always be ready to adjust current settings to beat the averages while improving process stability with controlled optimisation.
Without the input from subject matter experts (SMEs), you have data with limited insights around how best to leverage it. The back‑and‑forth process, between data scientists and SMEs, is what demystifies the data analytics ‘black box’ – leading to consensus and action plans that can be understood and justified across the organisation, and most importantly, at the frontline.
Standard analytics tools are quite complex and require data science expertise. Our team at DataStories delivers an easy‑to‑understand tool to internalise insights. This, in addition to involving SMEs early and often, greatly accelerates our rate of implementation to guarantee ROI and overall program success.
We ensure the technology used fits the need and that operators effectively use it to deliver desired outcomes.
Many organisations lack the alignment, capability and willingness to implement required changes. To make advanced analytics improvements last, 75% of the focus should be on the frontline understanding what the data is telling them, why it is important and how they can effectively use it to improve.
To ensure model insights are fully integrated and used effectively to improve daily decision making while driving high performance, the frontline must be fully upskilled with robust training and on‑the‑job coaching. Roles and accountability should be clearly defined and key stakeholders aligned. KPIs tracking progress towards targets should be established, made visible on performance dashboards and regularly reviewed.
A robust data architecture and infrastructure must be established to ensure data flows continuously update the model, and data collection limitations are proactively addressed.
Demonstrating value through a successful analytics implementation in one area facilitates buy‑in across the organisation – making a powerful case to identify new use cases for prescriptive analytics, either within the existing site or extending to other sites or regions.
Significant performance and stability uplift achieved and sustained by the operations is what contributes to retention strategy. It requires upskilling and intellectually challenging process engineers to ensure they are retaining systematised knowledge about how best to run the plant given daily changing conditions.
‟The best feedback I ever received was: ‘Wow. For the first time, I actually believe in technology. I now believe that when done right, technology can solve a complex problem’ That demonstrates the power of analytics. When done right the analytics can help find the solution to a difficult challenge.”
Juan F Ferrara
With our client’s best interest at the forefront, we begin by exploring organisation readiness to embark on an analytics journey, providing a detailed roadmap to close gaps that may hinder success. Leveraging tools that are value‑driven, systemic and intuitive rather than those understood only by data scientists, we offer a distinctive capability through data analytics consulting for organisations. Maintaining, from day one, a laser‑focus on delivering value that is transparent and actionable by the frontline.
Our acquisition of data analytics firm DataStories has enhanced our ability to help our client partners maximise performance and open‑up new sources of growth. At the heart of the DataStories platform is an AI‑based tool that enables organisations to understand and analyse data, and then rapidly turn information into Virtual Experts that provide strategic and operational insights.
10-20% fully locked in throughput improvement
1.5-4% of recovery improvement
20-30% of quality improvement
‟The biggest challenge we see in Prescriptive Analytics initiatives is that there is not enough focus on the business case we are trying to address. Our approach is to first confirm that it is possible to apply Prescriptive Analytics to solve the problem, conduct a proof of value to confirm that initial hypothesis still holds and then roll-out to other sites or use cases.”
CEO at DataStories.com
‟Prescriptive analytics, wired into a business and serving stakeholders daily, holds the key to consistency, transparency, and adaptability in an environment of constant change. We will see this play a key role in holistic industrial automation and fully embedded optimisation across the value chain over the next 10-15 years.”