When it comes to demand forecasting, most companies have way too many forecasting mechanisms in play across their organization. Each segment of the business ends up siloed from the others, relying on its own data and analysis, which impacts both efficiency and effectiveness.
Most organizations do a poor job forecasting, with just one in five coming within 5% of forecasts. This statistic is staggering, and it implies that although many organizations understand the value of forecasting, the majority of them are doing it inaccurately.
Traditional retail may be doomed, but its complexities extend far beyond common scapegoats, the Internet and eCommerce. The retail industry is more dynamic than ever before, and it’s driven by customer preferences and demand.
The vast majority of organizations consider data preparation their biggest bottleneck. It costs billions of dollars and delays discovering insights. But reliable data is a necessity in advanced analytics and without it, analytics solutions results are incomplete, or worse, inaccurate.
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