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The Role Of Big Data And Analytics In Supply Chain Management

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Supply Chain Management is one among those fields where big data and analytics found obvious applications. In the recent years, however, the businesses identified the potential of big data analytics and start implementing it in SCM than in other areas of operation such as business marketing or manufacturing. Most of the top rated companies analyzed the benefits of implementing big data in SCM and how it can positively impact the company’s overall financial and operating performance.

Big data analytics

When businesses implement big data in Supply Chain, they have high expectation and in some cases, many of the companies too face difficulty in adopting it.

According to the survey conducted by Accenture, 97% of the senior executives understand the need and benefits of implementing big data into SCM, but only 17% have implemented this strategy in one or more of their supply chain functions. Accenture further found that on an average of one-third of executives are engaged in serious discussions to apply analytics in SCM and three out of the ten have an initiative to employ analytics.

Accenture conducted a web-based survey that involves 1,014 senior executives from top global companies and 54% of the respondents held of C-level titles, including chief supply chain officer, chief procurement officer, chief sourcing officer, chief operations officer and chief operating officer and the remaining 44% of the crowd involves senior-level supply chain and operations executives. As per the web-based survey, 48% of the surveyed executives are interested in applying big data and analytics into supply chain, which helps them to gain better insights about the future. Nevertheless, the big data analytics can have a high impact on organization overall performance.

The main reason behind the popularity of implementing big data is that manufacturers are devising 80% of their supplier network activity using big data and cloud-based technologies to get requisite details beyond the limitations of Enterprise Resource Planning (ERP) and Supply Chain Management (SCM) systems. This strategy is highly beneficial for businesses whose models are designed for delivering order, shipment and transactional data. As the existing strategy fails to meet the challenges supply chains face today, it is the high time to think and implement new strategies that not only address the existing challenges, but also optimize the overall business operation.

“You can have data without information, but you cannot have information without data.” – Daniel Keys Moran

Being this as a current trend, let us have a look on top 10 big data analytics that revolutionizing Supply Chain Management!

Big data business scientist presenting the concept

  1. Scale, Scope and depth of data

The scale, scope and depth of data in supply chains are accelerating day by day, which delivers an ample set of data that drives contextual intelligence. Below given graph defines the 52 different sources of big data that are obtained through supply chains. The graph represents the different data sources that are generated on the basis of variety, volume and velocity under different levels of structured and unstructured data.

Big data supply chain graph

As per the above graph, it is clearly visible that majority of the supply chain data is obtained from outside sources. Hence, the point being very clear that it is a high time to concentrate more on outside sources as it directly impacts the results and has the potential to generate maximum data

2. Optimizing Supplier’s network

Big data enables challenging supplier’s network to focus directly on knowledge sharing and association, which optimizes the network to form, grow and propagate into other markets and establish over-time. Big data and analytics not only help supplier network to focus on transactions, but also helps creating a knowledge-sharing hub, which is obtained through the insights of big data analytics.

Big data in SCM

Above picture represents that the development of supply chain from networks, where sharing the knowledge becomes priority.

3. Optimizing supply chain capabilities

When big data and advanced analytics are implemented into supply chain successfully, it can optimize supply chain capabilities such as demand forecasting, supplier collaboration, integrated business planning and risk analytics at a quickening pace. According to the report generated by Delotte, control tower analytics and visualization are in the pipeline of supply chain that runs with big data pilots.

Supply chain capabilities

4. Disruptive technologies of Supply Chain

As per a report, 64% of the supply chain executives believe that big data analytics acts as a disruptive and the most significant technology if it is set for a long-term. Below graph defines how the senior executives prioritize big data over other technologies.

Disruptive technologies

5. Use of geo-analytics

As per the reports generated by Boston Consulting Group, big data can be efficiently implemented into Supply Chain Management to merge two complex networks and optimize then using geo-analytics. According to the report, combining geo-analytics and big data reduces the waiting time drastically and augment the efficiency of overall communication thereby augmenting the transactions within the network. Besides, high accuracy in the network is an added advantage.

Big data geoanalytics

6. According to the Accenture Global Operations Megatrends Study, implementing big data and analytics into SCM augments the supply chain efficiency by 41% and the integration across the supply chain will rise to 36%.

Big data company analytics

7. According to the Accenture reports, entrenching big data analytics in supply chain operations augment its process by minimum of 1.3x over using big data on an improvised basis. Source: Big Data Analytics in Supply Chain: Hype or Here to Stay? Accenture Global Operations Megatrends Study

Big data analytics. 1jpg

8. According to the One Network Enterprises, advanced big data and analytics has the potential to generate real-time visibility across SC which augments all the elements associated with it. Source: Turn Big Data Into Big Visibility.

Big data analytics outcome

9. Less time and more efficiency: Big data has the potential to generate a huge set of data through numerous sources. Besides, it has the potential to augment traceability performance and reduce thousands of hours of working time to access, integrate and manage the data thereby accelerating the work efficiency.

10. Increases supplier quality through supplier audit and to inbound inspection with final assembly of big data.

“Information is the oil of the 21st century, and analytics is the combustion engine.” – Peter Sondergaard

4 thoughts on “The Role Of Big Data And Analytics In Supply Chain Management

  1. It is very detailed analysis about how can big data and analysis play to enhance the capabilities of SCM, because this strategy believes in sharing knowledge is good. Many C-level and senior level executives have also shown their interest in this strategy, so that following advantages can impose positive impact on company’s overall financial and operating performance:
    1. Getting requisite details beyond limitation of ERP and SCM.
    2. By using geo-analytics, this strategy reduces waiting time, augment the efficiency of overall communication as well as high accuracy can be achieved.Real time visibility across SCM can be possible, so that it’s process can be enhanced by about 1.3 times and traceability incresed.
    3. Reduces thousands of working hours.
    4. Integrate and manage the data more efficiently.
    5. increases suppliers quality.

    There are couple of disadvantages are there like:
    1. High expectations
    2. Difficult to adopt because lack trust about this new strategy.

    So in my opinion adopting this strategy is very good idea, it is definitely not a risk. It is a opportunity to explore the all the factors which is very significant and useful can merge into SCM system, so that overall and sustainable growth can be achieved.

  2. It was very nice & proven facts. Survey tells us only 17% of them have implemented have implemented big data into their supply chain functions while 97% of them are aware of the importance. Why?
    – Comparatively, it should be cost effective
    – Availability for even small sized companies
    – Bring more awareness to the existing companies through campaign management & digital media. The importance has to be educated to core operations team since survey says executive team is aware where as blending data on regular basis is middle level & operations.

  3. Big data play an important role in diversifying the supply chain management, but it can be seen that only 17% of the 97% have implemented it. They might be facing the following problems or challenges:
    1. The logistics experts lack the expertise to analyse the large volumes of data,
    2. Managers might me having massive amounts of data but do not know what to do with it.
    These challenges can be overcome by working with people of range analytic skills and knowledge and ensuring that the analytics are embedded in supply chain operations.

  4. Undeniably big data now a days is playing a major role in SCM of every industry and is more likely to play major role in future as this trend is set up.Listing some of pros and cons of big data in SCM.
    1. Tracks the spend of single penny and gives alarm and corrective action to prevent the wastage.
    2. Forecasting made more accurate.
    3. Negotiations receive a better ground.
    4. Could be used for small, medium and large scale industries.
    5. Will surely lead a way to profits.
    6. Possesion of great amount of information which may lead to big management decisions for investment.
    7. Easy accessibility to every information.

    1. Will take time to capture the current market.
    2. Whole new department is required to work on data.
    3. Risk of insider trading or leaked confidential data.
    4. Less proffesionals in market at this time.

    Having said that, everything while it starts takes it’s time but the benifits offered by it compells others to give it a try.

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