AI Forecasts and Trends
Forecasting today is a cumbersome process that is still based on intuition rather than fact. Through applying machine learning techniques, models can be trained to address different aspects of the business to understand microtrends, identify anomalies and to forecast of course. From revenue forecasts, to price negotiations, to early warnings for churn to the impact of sales strategies on margin, cashflow and more. An ML powered forecasting APP for every business decision.
Connecting the dots
Reports in today’s world are historic, pegged to KPIs that often have no relation to the world we work in today and (worst of all), provide business leaders a siloed view of business performance. Sales reports for sales, financial reports for financial teams and so on. But by connecting the dots across all the data sets, we present users with information on the relationships across each function.
92% of executives are worried about making big decisions. With the deluge of data - executives are presented with on a daily basis, they are going information blind. How can they make decisions based on historical reports, outdated KPIs and lack of context? ‘Connecting the data dots’ is the basis to understand decision context & causality. These automations give executives greater insight into how decisions affect business outcomes.
Far too often, businesses record the last data in any transaction. A record of history rather than the journey of transformation the data took. This means that it is impossible for businesses to analyse how their data evolves over time, leaving them with a static view of what happened. At 3RDi we take snapshots of any changes in the data, allowing us to time travel across the data, do pick up any trends and anomalies that help us to assess performance.
Using simulations, our users gain greater insights into how their decisions affect business outcomes. What if we focus on our key accounts to increase the possibility of higher revenues? How will this affect our product strategy, or what does it mean for our margins? Or do we even have the resources to deliver what is needed? Our simulations help users to plan through scenario outcomes and to make the right strategic decisions
If a picture is a 1000 words, is the same true for a pretty chart? No. There is too much left for the users interpretation of any visual representation of data. What is missing is the context. Applying Machine Learning to clean, connected data, gives models that provide users with automated analysis & insights.
When 84% of the CEOs dont trust their data, you know you have a problem. Organisations are getting geared towards being more data driven. With Artificial Intelligence, Machine Learning, Deep Learning on the move the choices are to step up or step out. You need to improve the confidence business leaders have in their data with technology that identifies & removes bias. This increases forecast accuracy and helps reps to deliver their targets.