5 Common Data and Analytics Mistakes and How to Avoid Them

  • Written by admin
  • Dec. 11, 2017

    Even with the best software and logistics experts at your disposal, supply chain optimization is no easy task. And in the world of complex, interconnected supply chains, pitfalls in the optimization process usually come back to data in one form or another. Here are five offenders that trip up businesses.

    5. Thinking that More Data is the Answer

    Supply chain executives are already swamped with data. It comes from every direction—supplier ERPs, edge devices, Internet-of-Things sources, and more. More data alone is not the answer.

    Instead, businesses need a way to better manage their data. Software solutions that tie the supply chain together from end-to-end and normalize all information are how process efficiency is achieved. They’re  must-haves to corral the massive amounts of data that each company owns.

    4. Failing to Include Metrics in Operations Planning

    Even when end-to-end supply chain visibility is achieved, it can be tricky to know how to integrate the available data into the company’s operations planning. Specific metrics such as routing time, order volume, and vendor capacity can heavily influence how much inventory each touchpoint can handle and whether each supplier will be able to achieve consistent service level performance. Visibility solutions are the answer here—by taking a holistic view of supply chain operations, it becomes a simple task to see how suppliers work together and how to leverage available metrics to support operations.

    3. Incorrect Shipping Data

    This is a particularly troubling mistake for entities with multiple warehousing touchpoints. Accurate processing of inventory at each warehouse location requires that businesses configure their shipments such that they can be sent, received, and logged into each warehousing ERP. And unfortunately, this type of consistency is hard to find. Businesses need to have visibility into each of their shipping, distribution, and warehousing touchpoints to ensure that all shipping data is predictable and consistent. Supply chain research suggests that companies who achieve this level of integration outpace their non-integrated competitors in growth by 20 percent.

    2. Forecasting Inefficiency

    Accurate forecasting is always a challenge. Of course, historical data of past performance can improve forecasting accuracy, but only when the entire picture is viewed as a whole. Having performance data from only a few key suppliers only reveals part of the puzzle. To ensure that the forecasting is as accurate as possible, business owners must have a software system that provides insight into every aspect of the supply chain, from OEM to customer, in a structured and disciplined way.

    1. Lacking Visibility

    Perhaps the biggest data mistake a company can make is not making use of its data at all. Not intentionally, of course—but without a software system that provides end-to-end visibility of all touchpoints, data often gets neglected. And for large, multi-party supply chains, this missing data can be significant. Research by Aberdeen Group shows that the two biggest factors influencing the push toward visibility are the increasing challenges of managing complex supply chains (45 percent) and the desire for improved supply chain accuracy (43 percent).

    Despite the prevalence of these mistakes, they can all be avoided with new types of supply chain visibility solutions such as ChronosCloud. By assessing, normalizing, and creating a chronological timeline of every order that travels through the sales pipeline, business owners can prevent themselves from falling victim to any of these data mistakes ever again.

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    Is your business struggling with one or more of these common data and analytics challenges?

    See how you can benefit from an end-to-end cloud based platform for multi-party supply chain visibility across companies and time zones – click to learn more and schedule a free consultation.

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