The Propel journey started almost a decade ago, as an ambitious idea to shift from the soft and subjective nature of cultural and behavioural management to an approach centred in hard analytics. This was an extensive analytical challenge, taking years of real-world research and development to perfect. Today, Propel is an international success story and taking hold in South Africa.
As a next-generation workforce tool, Propel uses a sophisticated set of algorithms, un-gameable surveys and decades of behavioural science expertise to scientifically measure optimal mindsets & behaviours and link these directly to KPIs and revenue.
Is there really value in analysing mindsets and behaviours in the workplace?
Propel has shown that mindsets and behaviours can statistically explain as much as 40% of KPI performance in non-trivial roles. In an area that was previously subjective and unquantifiable, this represents a 40% information edge for leadership to align efforts at scale.
Having been built in-house from a data science perspective, the development methodology is entirely data-centric, every angle of the process can be queried in relation to every other angle, and every possible question is available to be answered through analytical interrogation. Additionally, being cloud-based means Propel integration into lines of business entails minimal IT headaches.
Propel has long since established a successful footprint across the business banking sector in Australia. The data-centric nature of this industry has allowed for accelerated, real-time development. To date, Propel has shown tens of millions of dollars in ROI. Moreover, it has become an integral, statistically relevant source of insight for leadership, into the key mindsets and behaviours that drive banking performance.
As Propel begins to take hold in South Africa, it is poised to be a valuable and highly accessible solution for any business. It provides hard insights into the untapped world of mindsets and behaviours for organisations trying to change culture and improve performance through machine learning.
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