SigmaWay Blog

Big data analytics in the pharmaceutical industry is changing drug development and delivery. Enormous volumes of data enable a pharmaceutical company to make more informed decisions and work much more efficiently.

Predictive analytics facilitates demand estimation and proper supply chain management, hence ensuring drugs are always available. Personal medicine ensures that treatment is given according to the individual patient's condition and is therefore effective. Real-time analytics in clinical trials run the changes with patients, and on time, spot any emerging problems, hence fast-tracking drug development. Big data also plays a very key role in discovering side effects and improving the safety of drugs.

In the future, as data analytics further develops, it could be that, by the big strides ahead in the treatment of pharmaceuticals, there are more effective treatments and better health outcomes for all.

To gain the edge in competing business world, one requires operation efficiency and it can be achieved by improving each step of supply chain. To do so following pointers can be used:

·         Cloud Based System

·         Communication

·         Dashboard Reporting 

·         Automate Purchasing

·         Vendor Performance

·         Cost Awareness 

·         Checkweigher

·         Transparency

Read the complete article here: http://it.toolbox.com/blogs/understanding-crm/ways-to-improve-each-step-of-the-supply-chain-73297

Big data Analytic can give real time analysis of huge, complex and continuously increasing dataset. It can be applied to many Business operations .But companies do not use this potential of big data analytics to supply chain management. Company can control the inventory and other supply chain operations more efficiently with help of analytic .for instance, companies can use unstructured data set in the inventory, forecasting and transportation for analysis and new insights can be delivered, like forecasting next date for restocking in supply chain planning. For the last 2 years big data had been used in the supply chain management but there is still a long way to go.

To know more read article by Bernard Marr : http://www.forbes.com/sites/bernardmarr/2016/04/22/how-big-data-and-analytics-are-transforming-supply-chain-management

Big data analytics plays an important role in supply chain management. 97% of supply chain executives have reported how big data analytics helped them to grow their business and only 17% of any particular industry have implemented this process. This process generates higher visibility and deeper insight to the customer behaviour and demand supply scenario. It also helps to discover and manage supplier relationships more effectively. Big data help to understand customer needs and make a 360 degree analysis regarding marketing channel, segmentation and acceptability. Predictability helps to create more efficient supply chain progress (increased ~10%). It identifies supply chain risk by considering the previous demand, supply scenario almost accurately. Supply Chain Traceability and recalls are data-intensive and highly correlated to supply chain risk. The ability to quickly meet customer fulfilment is an important driver. It helps in competitive advantage across all industries which can be achieved by big data analysis.

To read, follow: http://www.computerworld.com/article/3035144/data-center/overcoming-5-major-supply-chain-challenges-with-big-data-analytics.html

FP&A and S&OP are the two most essential processes for every organization. In modern times both have developed successfully and have started to take part in managerial decision making processes. The advantage of FP&A is that it envisages the results of the decisions that the organizations undertake. It achieves this by scrutinizing both the past performances and present activities and hence it makes the data readily accessible wherever required. While S&OP being one of the integral components of supply chain management, reduces the inefficiencies of the supply chain. It helps the firms to alleviate risks. FP&A on the other hand, manages everything from budgets to predictions. Therefore, both are equally important to a business for running efficiently.

Read more at: https://channels.theinnovationenterprise.com/articles/fp-a-or-s-op-which-adds-more-company-value

According to Burton White (Vice President of the Industry Supply Chains at Chainalytics), for retailers and e-commerce firms, developing an effective and efficient supply chain strategy is challenging. To make last-mile delivery as their core supply chain strategy, they have to provide right inventory at the right time at the right place in the right form.
Some tips to be considered while developing a supply chain strategy are:

• Never lose sight of what actually matters to the customer
• Explore innovative approaches, like to bundle product shipments.
• Explore non-traditional distribution capabilities.
• Optimize transportation solutions to meet last-mile demands.
• Consider the inventory’s form, function and placement within your supply chain.
• Focus on returns management efficiency.

Read more at: http://www.industryweek.com/last-mile

According to Saritha Rai (Contributor), e-commerce companies like Amazon, Snapdeal, ShopClues, Flipkart etc. find innovative solutions to timely delivery of their products by collaborating with Kirana stores, Dabbawallas in Mumbai, post office for reaching especially in rural areas and gas stations in Delhi and Mumbai. In a Morgan Stanley Report, Indian e-commerce market is expected to boom up to $100 billion in revenue by 2020. Timely delivery in the cities of India is a big challenge for e-commerce firms as roads are congested, streets are not numbered sequentially and customers many times don’t write zip codes or landmarks.  Finding these innovative solutions will not only benefit the e-commerce firms but it will also benefit local sources. To know more about these innovative solution read at: http://www.forbes.com/sites/saritharai/2015/04/15/from-dabbawallas-to-kirana-stores-five-unique-ecommerce-delivery-innovations-in-india/

Amazon launches new supply chain management technique “Dash Button” which allows the customers to order products automatically at the actual point of use.  According to Paul Myerson (Industry week), Amazon’s new launch Dash button puts pressure on the retailers, especially grocers who have very small profit margins (1-2%) and have a huge impact on the retail order fulfilment process.  This will bring a new concept called focusing on value to the customers and eliminating waste not only in the business environment, but now at the actual home of the customers. To know more about dash button read at: http://www.industryweek.com/inventorymanagement/amazon-dashes-make-consumers-and-their-supply-chains-leaner

 According to Dave Blanchard (Industryweek), customer’s demands for lower delivered costs are seen to be a big challenge. But, by using predictive analysis, we can identify patterns and predict future events. An organization using predictive analysis can make better decisions. George Prest (CEO of MHI) says that companies that continue to use traditional supply chain models will struggle in the future.  According to the MHI/Deloitte study, it was found that less than 25% of companies have adopted predictive analytics though that number is expected to climb to 70% over the next three to five years.

 Read more at: http://www.industryweek.com/supply-chain/predictive-analytics-let-manufacturers-see-more-clearly-their-supply-chains

Some strategies haven't succeeded dealing with supply-chain management. The reason is the cost of hiring expert workers. According to researchers the union of data science, predictive analytics and big data likely to alter the way in which supply chain managers lead and supply chains function. They named this as DPB. Companies have used datasets to plan ideas to meet customer demand. But now they combine external data to better estimate future risks .two points to judge analytic skills: 1) Data science and domain expertise are not mutually exclusive: Analytical skills are important for data scientists who focus on Supply Chain Management (SCM).2) that doesn't mean theory doesn't apply: Strong theoretical knowledge is essential in SCM. Use of suitable theory to build models before operating predictive analytics is key to justifying a circulation of false positives. The three links in supply chain: manufacturers, retailers, supply management, shipping management and human capital. Read more at: 

http://sloanreview.mit.edu/article/are-predictive-analytics-transforming-your-supply-chain/

According to a new survey conducted by Deloitte, it is found that as complexity in global supply chain networks continues to increase, less than one-third (26 percent) of business executives are using data analytics tools and processes to help manage third party relationship risks.Thirteen percent of those surveyed are still learning how to use analytics software and 22 percent use no data analytics at all. Few market leading companies leverage advanced data analytics tools and forensic accounting to identify anomalies in their transactional data & getting astonishing benefits while rest are lagging far behind in this issue. Nearly one-third (31 percent) of business executives surveyed, said that their organization has faced supply chain fraud, waste or abuse in the past 12 months.

Mark Pearson, principal, Deloitte Financial Advisory Services LLP, speaks about why organizations need data analytics to tackle supply chain fraud. To read more, please visit the following link:

http://www.net-security.org/secworld.php?id=16641

Organizations have implemented various software solutions to manage many processes, from ERP to power consumption to supply chain management. But when it comes to the most critical component of supply chain management – “Human Capital”, many companies are still playing catch-up. However, nowadays more organizations are turning to labour optimization solutions. These solutions not only keep track of operations, but also use predictive models and algorithms to determine future labour needs. Labour optimization software also analyze orders and resources to predict warehouse throughput. Then it automatically schedules the right balance of full-time, part-time, and temporary workers to meet demand. Managers receive alerts when labour levels don’t meet requirements. Optimization solutions have been used successfully for years in operations such as call centres, which needs to examine historical call patterns to predict future call volumes and ensure that they have the right people with the right skills in the right channels. Such intelligent technology has enormous potential in a manufacturing setting, helping companies do more with less.

To read more about this aspect, please visit Tracey Schelmetic’s article link as given below:

http://www.thomasnet.com/journals/techtrends/articles/labor-optimization-solutions-make-best-use-of-human-capital