Power Supply Chain Transformation with Active Intelligence

Power Supply Chain Transformation with Active Intelligence.

According to research, due to factors such as the epidemic 해시게임,

32% of businesses suffered revenue losses due to supply shortages,

11% of businesses said their brand was damaged as a result.


At the same time, many supply chain companies have also encountered some difficulties and challenges in transportation and other aspects.

In the past, most supply chain management construction solutions focused on cost-saving or improving cost performance.

The impact of epidemic and other environmental impacts will cause production shutdowns, the bankruptcy of suppliers,

So 93% of supply chain executives say they will increase the level of resilience across the supply chain,

It’s not just about the cost.

Shortages and disruptions in supply chains also contribute to inflation.

It is reported that the global cost of materials and raw materials has increased by 15% to 35% in recent months.

This was the largest increase since 1970.

At the same time, 75% of companies surveyed said they are paying attention to weather changes,

And invest in sustainable practices, including addressing extreme climate change, for a truly global corporate resonance.

Based on these backgrounds and trends, supply chain management and operation teams have to face new challenges.

Business executives want more data to support their business decisions,

Achieve full supply chain visibility and agility; budgets are also severely constrained due to reduced revenue and uncertainty,

They have to do more with less.

For industry practitioners, there are also challenges in real-time decision-making,

On the one hand, the remote office mode makes communication and collaboration less efficient.

At the same time, in order to improve the service experience of customers, indirectly leads to an increase in costs;

On the other hand, due to rapid business changes and changes in demand uncertainty,

It has greatly improved the requirements of enterprises in terms of management level and sales forecasting ability.

To address these business challenges, supply chain leaders are increasingly realizing the importance of business intelligence in management decision-making.

More real-time active intelligence

The traditional passive business intelligence based on historical data is gradually evolving into real-time actionable intelligence that focuses on process analysis.

Data discovery and insights under passive business intelligence are provided to users through independent dashboards and reports.

That is to say, its focus is on the operation of the enterprise, the performance of the supply chain and suppliers,

It is necessary to actively visit the website through the browser, and manage and use the foreseen content.

From a data perspective, business intelligence in the traditional way mainly provides historical views based on business data.

For many traditional banking or medium-sized enterprises, the business situation that occurred the day before is usually processed in the early morning or the next morning.

such as data warehouse updates. It is reflected in the front-end business intelligence or decision analysis layer, often referred to as “T+1” time.

Most of the systems provide information services in the form of data APIs.

However, it is not possible to directly turn these findings and data KPI changes into insights that affect decision-making or affect downstream systems.

In contrast, in active intelligence, some of the analyzed content can be embedded into the user’s own business system.

That is to say, there are some analysis contents in the system at the same time, you can use the data without switching different systems, find problems,

Bringing a better experience to users will also allow users to naturally establish a data-driven awareness.

From the perspective of different data sources, active intelligence provides a more continuous feature of acquiring real-time data.

It can make the data more real-time, and the analysis more timely and forward-looking,

And then build a more complete and flexible analytical data pipeline.

More importantly, active intelligence is not only the information provider and display side,

It also has the automatic transfer of applications,

such as the function of directly calling some downstream inventory management systems,

Realize the adjustment of goods between different warehouses,

find problems such as inventory shortages, and do not require manual participation.

Active intelligence includes the acquisition of raw data, the release of data insights,

Find key data, understand data, and act to influence these stages.

Through active intelligence,

enterprises can unlock the huge insights and business value contained in them in a more timely manner,

based on the generated data and driven actions.

Through the analysis system, enterprises can not only obtain this information and find problems but also based on these problems,

Take automated actions at the most critical moments in your business to achieve more benefits.

“Active intelligence provides a relatively complete analysis data pipeline,

From data collection to processing, to data platform automation, to data understanding and analysis,

As well as applying analytics to downstream systems, every step will be covered in our Active Intelligence capabilities. ”

Four Use Cases for Active Intelligence

In the field of the supply chain, the first application that active intelligence can cover is predictive maintenance,

Minimize operational disruptions as much as possible, whether due to the impact of the pandemic,

Or a sudden shortage of raw materials, reducing the efficiency of order fulfillment and achieving greater operational resilience.

A second use case for active intelligence is in inventory.

More and more companies are using more than general analysis, simple comparative forecasts,

It will also use machine learning, an artificial intelligence-driven model to manage its own inventory.

The purpose of “out-of-stock prevention” is to maintain a more reasonable inventory level.

Ensure operational continuity.

The third use case is optimization planning.

The overall process of the supply chain is relatively extensive, from planning to production,

Coordination of all aspects, including raw materials,

inventory in transit, etc., will ultimately involve order fulfillment.

Enterprises will encounter the problem of how to better understand data in demand forecasting and network planning.

Businesses can leverage geographic analytics, machine learning, and greater automation to improve forecast accuracy and timeliness.

The fourth use case is about logistics.

With the help of active intelligence, logistics has more visibility,

Using IoT technology, the data in the sensor is extracted in real-time and analyzed accurately.

Delivered to the mobile terminal, allowing enterprises to better understand and analyze the logistics situation,

This will improve the efficiency of overall logistics transportation and order fulfillment.

Through some exploration of the fulfillment of historical orders and logistics line problems,

It can also help enterprises to formulate corresponding optimization plans to improve customer satisfaction.

Of course, enterprises can also continuously improve their own level from the management level,

Step up coordination with suppliers, share more data with suppliers,

Engage suppliers more fully in the performance and risk of enterprise supply chain management,

Achieve and maintain more continuous supply chain management.

Combining leading supply chain experience with a rich infrastructure and customer base in the local market,

Provide high-quality integrated supply chain solutions for cross-industry enterprise customers.

More of them serve B-side enterprises,

mainly providing warehousing services and distribution services.

In the past, it only served one industry, but the industries currently served include FMCG,

retail, high-tech, spare parts logistics, automotive, life science, medical, industrial, etc.

There are many industries and regional scenarios.

Therefore, the first pain point to face is how to fully open up the data of a certain site,

And serve the different supply chain systems of multiple enterprises.

At the same time, there are many different systems in the customer’s supply chain,

Such as transmission management systems, venue management systems, customer management systems, etc.

The accumulation and integration of data are very complicated.

What needs to be done is to first modularize the product, and then establish a unified data platform.

It should be noted that in the process of modularization,

it is necessary to be able to use data to serve customers internally at a large scale and to meet their individual needs.

When managing these operational data,

the data can be captured from the data chassis for comprehensive visualization.

When customers need other data-based scenarios, they can help them optimize based on industry experience templates.

With the help of data management intelligence, visualized management of warehouses across the country is realized.

About 5000 man-hours were saved in the whole data analysis, after using the template,

Greatly improves employee data productivity.

“Now it only takes 1-2 days to build a fully visual site,

Significantly improved operational efficiency and achieved the goal of reducing costs and increasing efficiency. “