{"id":34838,"date":"2023-09-26T15:01:20","date_gmt":"2023-09-26T14:01:20","guid":{"rendered":"https:\/\/digileaders.com\/?p=34838"},"modified":"2023-09-27T16:26:20","modified_gmt":"2023-09-27T15:26:20","slug":"what-might-happen-the-power-of-predictive-analytics-2","status":"publish","type":"post","link":"https:\/\/digileaders.com\/what-might-happen-the-power-of-predictive-analytics-2\/","title":{"rendered":"What might happen? the power of predictive analytics"},"content":{"rendered":"

For companies that want to advance from data curious to data committed, one of the most powerful places to start is to establish data ecosystem foundations (e.g. data collection and storage best practices, quality parameters, KPI setting, baseline literacy training, tools adoption and usage, etc.). Foundations that are essential to have in place in order to do remarkable things with regard to advanced analytics and AI\/ML acceleration.<\/p>\n

When you\u2019re just starting off, data wins might be things like\u2026<\/p>\n

Full access into organizational KPIs at departmental levels<\/em><\/p>\n

Weekly and monthly team ceremonies where leaders report on their metrics<\/em><\/p>\n

Use of dashboards and visualizations to convey data more powerfully<\/em><\/p>\n

Increased data literacy org-wide<\/em><\/p>\n

Data tools available and being put to use<\/em><\/p>\n

Quality issues continually being addressed and remediated<\/em><\/p>\n

Huge and important wins!<\/p>\n

But as companies advance along their maturity journey, how they want to win with data often starts to change. They begin to eye things like AI\/ML adoption and acceleration, progressive KPI-ing (more on that here<\/a>), eliminated data siloes, data science, automated analysis delivery and\u2026 for many\u2026<\/p>\n

 <\/p>\n

Predictive analytics. Or using data to shift from asking \u201cwhat happened?\u201d to \u201cwhat might happen?\u201d<\/strong><\/p>\n

Predictive analytics, at the simplest of levels, is about leveraging advanced analytics and modeling techniques to make predictions about the future\u2026 future outcomes, trends, events, performance, etc.<\/p>\n

Companies can leverage predictive analytics across so many different domains and focus areas from answering questions about buying behavior to supply chain management to product development to risk management and so on. In fact, it\u2019s become such a pervasive focus and investment of leaders across all domains that the predictive analytics market alone is expected to grow from $12 million in 2022 to\u00a0$38 million by 2028<\/a>.<\/p>\n

So, what steps can you take today regardless of the functional area you support? Here are a few quick tips:<\/p>\n