Some problems seem either too complex, unimaginable or too time consuming to tackle by throwing data at it. That is, until you consider the real-world possibilities of advanced analytics and artificial intelligence. The key here is understanding that the best applications of this always involve humans - art meets science to generate the best value. Litmus has a strong history of advanced analytics and machine learning to solve valuable and complex problems for its clients. From predictive models on the yield expected for a manufacturing process, the likelihood of customers to churn, bespoke forecasting solutions, strategic and operational segmentation to text analytics of hundreds of thousands of social media comments to understand market sentiment - these are the most challenging and rewarding problems which can really unlock understanding, profitability and inform decisions which provide genuine, unique competitive advantage. Let your data loose. Solve your thorniest problems and inform your gut feeling with high quality evidence.

Client Testimonial Quote & Job Title

"Harnessing the power of data analytics is going to change the business and focus people on the real opportunities. We are now delivering meaningful insights to our people, enabling them to take the necessary interventions. This approach is now being applied to help improve attendance and health & safety." Mark Leslie—General Manager of Operations, Silver Fern Farms (SFF) Optimising yield is one of the most important ways to maximise profit within the meat industry. Until recently, Silver Fern Farms would mainly forecast yields on an annual basis and set targets accordingly. But offal yield changes monthly or even daily. Silver Fern Farms found its yield models weren’t sensitive enough to detect factors that could affect how much meat came into its plants, such as climatic conditions leading to drought or condition of animals. Although the business was rich on data, it was poor on information and Silver Fern Farms found staff needed more support to draw actionable conclusions from the data. Implementing our dynamic yield solution; ‘Yielded’, we took years’ worth of internal, historical data and overlayed this with external data such as NIWA climate information and farm specific data. For the first time, the business consolidated silos of information, with algorithms considering multiple factors and predicting yield, allowing Silver Fern Farms to predict yield more accurately before processing. This prediction was turned into a simple PowerBI dashboard displaying the accurate target yield for each item. Actual results were shown on the same dashboard with comparisons to the expected yield and to ‘Best in Group’. This allowed each site to see how they are performing against their own expected target, together with what best practice is across the group. Machine learning checks the accuracy of the forecast and identifies anomalies in the results for further investigation and refinement. Providing these insights is only part of the solution, it supported the design of the intervention process. Coaching the Leaders and staff to use these insights is the bit that delivers the bottom-line benefit. Daily and weekly routines were implemented to engage the team with how they were performing using accurate information, identify opportunities to improve and implement solutions.