{"version":1,"type":"rich","provider_name":"Libsyn","provider_url":"https:\/\/www.libsyn.com","height":90,"width":600,"title":"EP 169 | Why Good Estimates Can Still Produce Poor Reconciliation","description":"If your resource model is statistically robust, why doesn't it always reconcile with production? In this episode of Fresh Thinking by Snowden Optiro, Melanie Bulley and Senzeni Mandava Matondi explore why good resource estimates can still lead to disappointing reconciliation results. They discuss the impact of grade smoothing, explain the concept of conditional bias, and explore why reproducing the average grade is only part of the story. The conversation also covers practical techniques used by resource geologists to assess estimation performance and improve local predictions that support better mining decisions. Whether you're working in resource estimation, grade control or mine reconciliation, this episode offers practical insights into bridging the gap between statistical accuracy and operational performance. ","author_name":"Fresh Thinking by Snowden Optiro","author_url":"https:\/\/snowdenoptiro.com\/","html":"<iframe title=\"Libsyn Player\" style=\"border: none\" src=\"\/\/html5-player.libsyn.com\/embed\/episode\/id\/42345035\/height\/90\/theme\/custom\/thumbnail\/yes\/direction\/forward\/render-playlist\/no\/custom-color\/88AA3C\/\" height=\"90\" width=\"600\" scrolling=\"no\"  allowfullscreen webkitallowfullscreen mozallowfullscreen oallowfullscreen msallowfullscreen><\/iframe>","thumbnail_url":"https:\/\/assets.libsyn.com\/secure\/item\/42345035"}