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How ParceLive gets users over the ‘big data’ analysis paralysis hump

on July 9, 2019 No comments

Whether you are a business-to-business Chief Information Officer (CIO) or a self-employed information technology (IT) guru, you have no doubt grown sick and tired of your employees and clients asking you about how to leverage ‘big data’, machine learning (ML), and artificial intelligence (AI) in their day-to-day operations.

According to SCM world, 64% of supply chain executives postulate that big data analytics is a disruptive and important technology, with long-term change in management structure inevitable.

What’s more, you are also certainly growing weary of having to constantly recover, repair, and make more robust incompatible stores of data that provide little, if any, value to the end user.

External supply chain managers as well as in-house, executive-level leaders are just as frustrated with this seemingly endless deluge of information that they are supposed to understand and use when making strategic decisions across global networks.

In order to move beyond this paralysis by analysis, companies no longer need to look to external databases or management information systems so much as select the right software that works not only across corporate boundaries, but geographic ones as well.

This vision of realizing an optimised supply chain is not only achievable for the smallest business owner, but a strategy that can result in a key competitive advantage for large, well-known corporations, especially when that operator or chief executive selects ParceLive by Hanhaa as the simple, yet effective, solution for information management.

Defining ‘Truth at Scale’ in the supply chain environment:

Data is both a blessing and a curse.

This is to say that collecting all of the ‘touchpoints’ throughout one’s warehousing, shipping, and stowing operations can be overwhelming and is, more often than not, an exercise in futility.

Data is not information until given meaning through either human-based analysis or smart ML pattern recognition. Even still, system outputs can prove underwhelming, inaccurate, or irrelevant when measuring the wrong ‘things’.

That said, and before implementing ParceLive tracking technology and data capture software, it is important for the IT specialist as well as the CIO to set out what exactly it is that he or she wants to measure.

By identifying these key performance indicators (KPIs) early and revising them often, the company can not only better understand their current ‘as is’ operational efficiency, but also begin to experiment around how to optimise their current routing or partners in order to scale into the future.

How ParceLive beats analysis paralysis: 

Once a company or owner-operator knows what to manage, then the transition to and implementation of ParceLive is seamless due to the fact that the software tracks an item’s journey from right off the production line to the customer’s front door.

What’s more, the tracker monitors and captures data around any changes in temperature, humidity, orientation, location, container integrity, and more.

Upon receipt of waypoints and other shipping elements, the software provides mapping insights into carrier performance, which can be shared with those brokerage firms toward better, faster delivery.

How ParceLive finds micro-patterns so you don’t have to:

ParceLive is more than just data capture, of course, as it offers the CIO, supply chain manager, or IT representative the power of ML in that the software can find micro-patterns that human analysts might miss, but that could still prove powerful when compounded over multiple, hourly, and otherwise routine deliveries.

By searching for and discovering unnecessary reroutes or delays, the company not only no longer has to pay for outsourced data insights, but can, instead, address any behavioural concerns internally.

Reducing minor deviations in shipping, standardizing routes, and providing clear insights into operations also means that ParceLive can act as both a means to passing internal as well as external audits with on-demand, easily accessible insights.

How ParceLive transforms business:

ParceLive also empowers businesses to grow, or scale, based on truth.

This is to say that when owners, operators, and CIOs know more about their performance, then they can target those areas that need more, or fewer, resources and where to reallocate funds in order to drive revenue.

Supply chain management is no longer simply about minimizing cost or reducing risk so much as realizing the competitive advantage they can offer when building goodwill between partner firms with reliable tracking and feedback, but also customers that get the right product at the right time in the right quantity.

Conclusion & call-to-action:

In parting, consider the following statistic:

Though storage solutions seem inexpensive at first, costs mount up fast when a company starts capturing all the available data produced by digital supply chains. A recent survey of nearly 1,500 Europe, Middle East and Africa (EMA) companies reported that a midsize company with 500 terabytes of data is likely spending roughly US$1.5 million per year in storage and management costs to support nonessential data.

Now ask, is this your small business or corporate policy?

If so, then perhaps your analysts are facing analysis paralysis in looking to find scalable opportunities in all of the truth that is your data and, perhaps, look to smart ML, AI, and big data in the form of ParceLive.

Free your personnel to think more strategically about how to grow the firm by leveraging such software to optimise, in real-time, through micro-pattern recognition.

Stephen hartnettHow ParceLive gets users over the ‘big data’ analysis paralysis hump