STANDARD BANK 2016 RUNNER UP - WILDEST INNOVATION

IDEASCALE

Standard Bank was established in 1862 and it is now one of South Africa's largest financial services groups, operating in 20 countries across Africa and other key markets around the world.

Standard Bank continues to position the group for the future, putting customers and clients at the center of everything they do. In line with the realities of risk, regulation, technology and competition that are shaping the African landscape, they are investing significantly in diversified operations, people and culture, systems and infrastructure, and their brand.

To that end, Standard Bank introduced Up Squad. Up Squad is an annual competition open to all PBB SA, G2, RoA, Channel and PBB Enabling Functions employees, during which they knowledge share their implemented innovations that they are using to change life in the Bank.

Standard Bank judged the success of this program by the number of innovation logged, as well as the number of comments and number of votes. In total, the campaign logged 233 innovations, 975 comments, and 4928 votes, but one of the featured ideas had a significant impact on the business.

The ATM-CIT Route Optimization Project Navigator used artificial intelligence (machine learning algorithms) to manage risk, cost, and service in the distribution and collection of physical cash in the ATM supply chain.

To plan CIT routes effectively, a route optimization tool is needed. However, ATM CIT planning requires a balance between maximizing service levels and minimizing costs. Most, if not all off-the-shelf tools focus on just minimizing costs, whilst costing millions to acquire.

To meet the business requirements at minimal cost, this team member built a bespoke route optimization tool.

The tool (dubbed 'Navigator') used a highly-customized, bespoke optimization algorithm that seeks to optimize service levels and reduce costs by varying degrees based on user-input. Due to the multi-objective constrained optimization problem, conventional route optimization algorithms weren't effective. As such, new techniques for the route optimization problem were developed in the process of creating this tool.

The tool was judged on its impact / business benefit, alignment to strategy, collaboration, novelty and discretionary effort.

But perhaps best of all this prototype tool reduced failure demand (i.e. downtime) significantly, between 20% - 23% in 2016, depending on the ATM service centre.

2IdeaScale Case Studies

Standard BankReducing Downtime by up to 23%