Forbes gives five ways to dramatically reduce the cost, complexity, and time it takes to build marketing performance models. Nobody in the marketing world argues with the potential for data and analytics to grow their business.  Big data promises more personalized customer experiences, targeted campaigns, and better optimization models. Marketers now spend 8% of their budgets on analytics and will grow that amount by double digits in the coming years. So how come most marketers can’t measure the return on these large investment in data and analytics? According to the Forbes there are several roadblocks that keep marketing organizations back from leveraging big data to achieve higher levels of marketing accountability and performance. In particular, CMOs identified insufficient tools and technologies to reduce the time, cost, and complexity of developing data-driven measures and models of marketing performance. “A big gap for us is the time it takes to model performance in terms of clicks, views and sales in a two-tiered distribution model,” according to Mark McKenna, CMO of the Putnam Funds. “We need to get on-platform and off-platform data from distribution partners to calculate attribution to sales and asset movement.”