Everyone has seen business cases for AI solutions, but fewer people have validated and measured the achieved business impact. It is true that sometimes the value of the “more accurate forecasting” or “deepen customer understanding” is challenging to measure. However, one of the key success factors for AI transformation is visibility to the management team, and one of the best ways to get management’s attention is numbers.
There are two types of business impact that companies can measure:
– Direct business impact: time savings & sales increase from delivered AI solutions. However, this is sometimes impossible to measure
– Indirect business impact: more accurate forecasting, better decision making, deepened customer understanding, etc
Last year, we built a solution to monitor the business impact of AI solutions even in almost real-time. In this presentation, I am happy to share learnings from this initiative for the wider data community. The key learnings are: selecting the projects where direct impact is possible to measure, but setting up a leading indicator for projects, where value is mainly indirect. It is possible to enrich and add elements from direct impact also to indirect projects if ensuring that everyone also understands indirect value. Finally, work together with business controllers and report achievements at least every month for the management.
Olli-Pekka Nieminen, Manager, Data & Digital Business Transformation | Konecranes
Olli-Pekka is an Innovation, data science & digitalization professional. During the past three years he has been focusing on Advanced analytics competence center ramp-up, especially in areas of portfolio management and culture transformation. Previously he has been working as company’s Innovation manager. He has also been a visiting lecturer at Aalto University and Tampere University about digitalization, industrial internet, and innovation management.