For over two decades, SIME has been a destination for leaders fascinated with digital transformation.
In the spotlight were the obstacles to effective data use. While most companies appreciate the benefits digitisation has brought — more data, insight generation opportunities and advanced tools to automate— many are (understandably) struggling to leverage them.
Stepping up to the stage, our chief scientist and co-founder, Michael Ross, explored the root causes of current business challenges, as well as how they can be overcome by adopting a new mindset. In particular, he emphasised the importance of mastering the ‘golden triangle’, where analysis creates insight that drives smarter actions, and fuels an ongoing cycle of continuous improvement.
For those who could not attend, here are some core takeaways:
- Averages are the enemy: In the past, blunt actions based on aggregated data were good enough, but now it’s time to move away from high-level averages. Managers can no longer simply look at an average outcome and rely on their intuition to determine which way they should pull the lever; a new hierarchy of metrics is required to understand performance and drive decision-making. Outliers, deciles, dimensions and stratification are critical tools for unravelling averages to unlock valuable insight.
- Getting the basics right: Companies need to recognise that boosting results depends on a well-ordered data store. So far, failure to prioritise data coordination has caused an instrumentation gap that stops them from gaining profitable insight. To keep progressing, businesses must shift their attention back towards building a robust data framework; capable of capturing the digital exhaust created by consumer activity, and combining data in a clean, holistic and joined up pool.
- The mechanics to go atomic: Businesses now have the chance to rethink decisions and operate at a much more atomised level; taking data evaluation right down to customer, SKU, store, SKU-store or even customer-SKU-store level. Successful activation requires an infrastructure that takes raw data through several layers of evaluation and augmentation to produce curated, comprehensive and useable insight.
- Human vs. machine: It’s important for every organisation to ensure its use of intelligent tools works for its sector, culture and people. Retail environments are typically dynamic, competitive and uncertain, and managing these factors calls for a specific kind of model. Successful businesses will be the ones that get humans to do what humans are good at, and machines to do what machines are good at. It is all about striking the proper balance of semi-automation that leverages the best of machine logic and efficiency, alongside human guidance and expertise.
All legacy businesses have evolved operating under constraints; including limited data access, ability to analyse and restricted resources. Now, digitisation has lifted these barriers and paved the way for deeper insight that enables higher performance. But embracing the new isn’t always easy. What’s essential in this new world of retail is fostering the culture, capability and courage that allows people to think differently and recognise the complexity of what's going on, all fueled by a new way of thinking in order to unlock limitless opportunity.