Manufacturers- How To Predict The Future & Not Bankrupt Your Business

Manufacturers and businesses, like elections, have for too long relied on an expert's voice to guide decisions and predict how the winds would shift in their favor. There was an allowance for expert driven decisions because every business operated this way. That meant every business could tolerate a certain number of poor decisions and continue to survive. But as big data is taking hold and decisions are being predicted based on information, the number of poor choices a business can make is quickly dropping. The analysis and subsequent decisions that used to be acceptable is leading to increasingly poorer performance relative to their competitors. Businesses that guess cannot survive in this analytical marketplace.

Not a believer yet? Consider this . . .

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Prior to the 2012 presidential election, there were countless heated debates against data scientists in the political domain. The poster child of the election data scientist is Nate Silver from the New York Times' blogsite Five Thirty Eight. Unfortunately, for the pundits who decried Silver's pragmatic approach, he could not have been much more accurate. His predictions on the US presidential race were accurate. Silver predicted every state correctly; 50 out of 50; 100% right. His successful analysis doesn't stop there, Silver continued to be spot-on in his predictions for nearly every US Senate contest. Silver's success should also have a profound impact on how businesses leverage data analysis.

It provides clear evidence that the business world needs to rely on measured performance and projection over opinion and spur-of-the-moment inspirations. Organizations should reject the so-called expert's opinion, that is based on instinct and outdated metrics, as a viable path to set the direction for decision making. This new era, based on more complex data models, has the potential to permeate into many areas of life.

Of course, this data driven approach is being fuelled by advancements in technology and software, such as SyteLine ERP. Our datasets have expanded faster than our ability to count them, processing capability has exploded through the use of the cloud, and outlets to display data have multiplied to include tablets, phones, and many more platforms. We are at the prefect intersection of tools and capability to deliver upon this possibility. We have the processing power and capability to deliver on it here and now.

There is another driving force that is just starting to gain momentum in the business space. Organizations are becoming aware that seemingly unpredictable events can be broken down and presented in a meaningful ways to project outcomes, and therefore impact decisions. As this concept gains more momentum, businesses of all types will need to find new ways to embrace predictive analytics. Organizations will need the tools and talent to identify patterns of behavior that, if left unchecked, could prove to be fatal to the health of the company. The stage is set for future success: businesses that know -verses- businesses that guess.

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