Information is now the main focus as a strategy for competition. Even today, few companies strive to accurately capture and use data to make business and operational decisions.
Some information about customer preferences, forecasting the volume of sales generation to optimizing operational capacity has become a necessity for managers to manage their business in today’s competitive era.
In this case, data is the biggest resource and power for companies to manage their business to achieve success.
However, the current availability of data is very complex. As a challenge, every manager must process data and sort it into accurate and relevant information in business decisions.
Especially in the digital age like today, through access to the internet today, which has been developed in various ways Internet of Things-IoT-, they all use Internet technology, the need for data can be obtained quickly and easily and in sufficient quantities. .
Value dimensions of big data
When companies use big data in their competitive strategy, the first question they ask is what kind of big data can increase organizational value? Based on the value aspect of big data information, there are 3 dimensions of using big data for business organizations, which include customer experience, new business models, and operational efficiency.
The use of big data for operational efficiency results from increasing transparency, improving performance and quality, and optimizing resource consumption. Companies can use the data to improve the quality of interaction with customers in using the company’s products and services.
Average data is doubling in the digital age
In the recent digital era, the available data has increased rapidly with an average of 2 times per year. For example, the amount of data available in 2010 was 2,000 exabytes, while in 2015 it increased to 10,000 exabytes. It is estimated that data volumes averaged 40,000 exabytes or more in 2015 alone.
In proportion to the increasing volume of data, the data also has characteristics that are significantly different from the data characteristics that occurred in previous years. Some of them are:
1. Data from devices connected to the Internet
The first large amount of data flow comes from various devices connected to the Internet, such as RFID, sensor networks, smartphones and webcams. All these devices
2. Very diverse and unstructured
Data Today’s data is typically unstructured and highly variable, such as blog entries, audio, images, e-commerce catalogs, and discussion forums. All of this data is large, diverse, and rapidly acquired. So that in its development it has now become a feature of Big Data. Today, companies analyze and manage Big Data to increase the value of informed business decisions.
Benefits of big data in logistics
Big data analysis provides many competitive advantages in the field of logistics due to the different features that can be effectively applied in the logistics industry.
1. Operational
Optimization Optimizing operational activities, including resource utilization, geographic coverage, and delivery time, is one of the strongest challenges in logistics. Even large-scale logistics activities require data for efficient logistics management.
2. Delivery of tangible goods
Delivery of tangible goods requires direct consumer interaction during delivery and Pick-up Goods on a global scale, the large number of points of interaction with customers every day can provide opportunities for product feedback, market intelligence and demographics. Big data can provide a versatile tool for generating valuable insights into public sentiment and the quality of the product itself.
3. Synchronization with business customers
Modern logistics solutions have integrated systems in production and distribution processes in various industrial sectors. With customer-intensive operations, logistics service providers tend to feel the pull of vertical markets, regions and individual businesses.
4. Information
The delivery network and transport network is the most important source of data in this case. In addition to using data to optimize these networks, data networks can provide valuable insights into flows in the global flow of goods.
5. Global coverage, local presence
Decentralized operations are essential in logistics services. Nationwide Transit has automatically collected a lot of local information on transit routes. The big data stream processing system in a large transport fleet provides a valuable representation of information for traffic, demographic and environmental statistics.
Big Data Big Box features to help you with logistics problems
With Bigbox’s advanced big data analytics system in retail, you can better understand consumer sentiment and behavior. You can experience your shopping in one Base of all channels and adapt to different regions. Can change prices and promotions dynamically. Additionally, you can enable supply chain fulfillment.
Big data from Big Box supply chain or supply chain. Where smart retailers rely on connected data based on external and internal demand to continuously improve the accuracy of demand forecasting and the accuracy of analytical models.