The forecast accuracy problem

I came across a recent ๐—™๐—ผ๐—ฟ๐—ฏ๐—ฒ๐˜€ article on forecasting accuracy that really resonated. It described forecasting as one of the toughest, most persistent hurdles in sales โ€” something that technology still hasnโ€™t solved.

The piece cited ๐—š๐—ฎ๐—ฟ๐˜๐—ป๐—ฒ๐—ฟ ๐—ฟ๐—ฒ๐˜€๐—ฒ๐—ฎ๐—ฟ๐—ฐ๐—ต showing that 67% ๐˜ฐ๐˜ง ๐˜ด๐˜ข๐˜ญ๐˜ฆ๐˜ด ๐˜ฐ๐˜ฑ๐˜ฆ๐˜ณ๐˜ข๐˜ต๐˜ช๐˜ฐ๐˜ฏ๐˜ด ๐˜ญ๐˜ฆ๐˜ข๐˜ฅ๐˜ฆ๐˜ณ๐˜ด ๐˜ฃ๐˜ฆ๐˜ญ๐˜ช๐˜ฆ๐˜ท๐˜ฆ๐˜ฅ ๐˜ค๐˜ณ๐˜ฆ๐˜ข๐˜ต๐˜ช๐˜ฏ๐˜จ ๐˜ข๐˜ค๐˜ค๐˜ถ๐˜ณ๐˜ข๐˜ต๐˜ฆ ๐˜ง๐˜ฐ๐˜ณ๐˜ฆ๐˜ค๐˜ข๐˜ด๐˜ต๐˜ด ๐˜ฉ๐˜ข๐˜ฅ ๐˜ฃ๐˜ฆ๐˜ค๐˜ฐ๐˜ฎ๐˜ฆ ๐˜ฉ๐˜ข๐˜ณ๐˜ฅ๐˜ฆ๐˜ณ ๐˜ต๐˜ฉ๐˜ข๐˜ฏ ๐˜ช๐˜ต ๐˜ธ๐˜ข๐˜ด ๐˜ช๐˜ฏ 2020. Harder, not easier โ€” despite the explosion of data and AI tools.

That says a lot about where we are as an industry. Weโ€™ve built increasingly complex systems to ๐˜ฎ๐˜ฆ๐˜ข๐˜ด๐˜ถ๐˜ณ๐˜ฆ the pipeline, but many teams have lost touch with the human signals that ๐˜ฅ๐˜ณ๐˜ช๐˜ท๐˜ฆ it.

AI can absolutely help โ€” itโ€™s part of the answer. But if weโ€™re not careful, it can also widen the gap between leaders and the reality of whatโ€™s happening in their deals. We end up automating the illusion of control instead of improving it.

The challenge now isnโ€™t to find smarter models. Itโ€™s to bring those models closer to the truth of how deals actually unfold โ€” the judgment, the context, the conversations that no algorithm can see.

Worth a read for anyone leading a sales organisation right now.

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