Retail Technology Trends

In the era of the customer, shoppers dictate what they want and how they want it. Today’s customers are intelligent, more market-aware, and have higher expectations. Empowered by digital devices and social networks, these customers want the opportunity to participate in the design process of the products and services they wish to purchase.

Research from 2015 suggests that one out of every three customers would like the ability to personalize the product that they are considering to purchase and will search for this ability when shopping. Fashion retailers are increasingly recognizing this emerging consumer demand and have begun to offer customized products and services. From RedThread using body-scanning technology to offer best-fit clothing to Louis Vuitton’s “Now Yours” customization service that allows customers to add a personal touch to their sneakers, several great examples have surfaced in the recent past that demonstrate how retailers are innovating customer experience to cater to the growing demand of personalization.

Delivering mass customization through technology

Mass customization is no longer an idea of the future; it has become a competitive requirement in today’s retail landscape. Most customers prefer to pay for customized products that allow them to express their individuality. Businesses need to leverage technology to offer product personalization at scale while also turning a profit.

In the past, it took several days or weeks to design and produce bespoke items, which increased costs and severely limited the output that a business could sustain. However, several modern technologies like direct-to-fabric printing, machine learning & AI, and 3D printing are now enabling affordable mass customization. These enabling technologies are disrupting the retail market and introducing new ways of giving customers the personalized experience they want.

Harnessing analytics for effective personalization

A successful product personalization service must include the options that your customers want. People would never come to your hundred-flavor ice cream parlor if they didn’t like any of the flavors. But how do you know which product features your customers want to customize? Which options should you offer for each product feature?

Before you begin offering personalized products, it is important to learn more about your customer. Advanced data analytics tools provide comprehensive, 360-degree customer visibility by mining actionable information about your customers through their past purchases and social media activity. Applying machine learning to these data reveals general trends and preferences that you can use to direct your product development efforts.

These tools can also be applied individually to each customer’s history to automatically generate designs that match their unique tastes. Imagine receiving an email every month from your favorite brand that offered you clothes designed just for you – their cut, fit, material, and color is just perfect for you. You’d be a loyal customer for life! The real value of personalization services is the enormous increase in customer lifetime value. Extending machine learning to MRP can help ensure that available inventory is sufficient to fulfill varying customer demand.

Retailers in general and fashion businesses in particular should invest in digital solutions that help them rapidly adapt to these changes in the retail market. HauteLogic, Visionet’s innovative solution for fashion and apparel businesses, is a cutting-edge end-to-end solution that combines machine learning, advanced analytics, partner communication, and eCommerce functionality to manage every aspect of your fashion business including planning, design, production, and distribution. Learn more about HauteLogic and discover how it can help you thrive in the age of disruption.

For over twenty years, Visionet Systems has been proud to serve as preferred technology partner for a number of leading global brands in the fashion, retail, consumer packaged goods, and financial services industries. 

 As a global Microsoft Gold partner, Visionet has provided innovative products, services, and thought leadership, with a solid track record in Business Intelligence & Analytics, ERP platforms, e-commerce implementations, and Enterprise Application Integration. 

The American Fashion & Apparel industry relies heavily on imports. Global suppliers and factories are an integral part of sourcing and supply chain operations. Building strong partner relationships and improving visibility across the supply chain result in higher reliability, flexibility, and agility.

"98% of clothes and shoes purchased in the US are imported."

To achieve this, focus on these key processes:

Vendor Onboarding

You need to establish a digital onboarding process to track new vendor requests, vendor profiling, and segmentation, as well as an approval workflow to automate and track vendor onboarding approvals. Critically, establish a self-service portal for vendors, factories, agents, and buying offices to work together during the sourcing process.

Supply Planning

You can easily share real-time supply forecast updates electronically with supply partners (suppliers, factories, and agents) through the cloud-based self-service portal. This enables factories to preempt fluctuations in demand and plan ahead collaboratively, which can in turn help improve lead times and expedite reorders in special circumstances.

Order Issuance

Your order issuance process needs to be completely digitized through the vendor collaboration portal. Issuing orders to factories and suppliers in real time on the self-service portal enables supply partners to respond in real time and reduce order issuance and confirmation delays. That way, you can communicate any adjustments in size breaks or delivery destinations for immediate planning and action. The vendor collaboration portal also improves supply chain agility by providing a tool that lets you push customer-requested changes down to vendors electronically.

Vendor Production Milestone Tracking

Every production department manages one or more production calendars for seasonal production planning and tracking across multiple brands and production groups. Production calendar indicators need to be tracked in the production system with real-time updates from your suppliers, factories, and agents through the self-service collaboration portal. Built-in reporting can help you preempt delivery delays and identify potential customer orders that may be impacted. Insights gained through milestone tracking can help you address and mitigate delivery risks, improve order fulfillment, and boost customer satisfaction.

You need an easy-to-use sourcing solution that enables you to execute collaborative supply chain processes via self-service portals for partners and vendors. HauteLogic by Visionet is perfect for supply chain integration and collaboration. Contact us today for a live demo to understand how our solution and services can help you achieve your goals.

Fashion & Apparel makes up a small portion of US imports but contributes to a disproportionate amount of the tariffs collected by the United States government. As the White House continues to hint at an expansion of tariffs to include a wide range of consumer goods that includes apparel and footwear, heavy reliance on imports is a major risk for the industry.

Few Fashion & Apparel retailers and designers have the capacity to establish in-house production, and creating that capacity in a short period is no mean feat. However, moving away from full package sourcing and outsourcing specific manufacturing processes to US factories is a comparatively easier and more manageable change in production operations that the industry can still explore.

Apparel, footwear, and travel goods represent 6% of US imports, but they contribute to 51% of the tariffs collected by the United States government.

The benefits of a domestic outsourcing production model are obvious: shorter lead times, the flexibility of easier in-season reorders, faster store replenishment, collaborative product design, more direct and on-the-spot quality control, flexibility in production capacity, centralized materials requirement planning (MRP), easier material safety and reorder point management, and, of course, lower tariff costs only paid for material imports.

However, there are many challenges that need to be managed for a successful transition:

Establish strong domestic partnerships with contractors and factories The single most important aspect is onboarding the right contractors and factories for serving your product lines and categories. Building strong partnerships is essential for securing consistent lead-time commitments from contractors and factories. This requires supply chain visibility by continuously and consistently sharing sales and demand plans of new product lines, reorder and replenishment forecasts, and contractors’ progress reports. It’s essential that you have a domestic production solution that supports such collaboration.

Define production control and material management processes If your organization relies entirely on full package sourcing, processes for MRP, material purchase, issuance, and consumption are non-existent. Therefore, you don’t have the skillset you need in-house to scale to domestic production. Implementing new processes should focus on recruiting and/or training the right internal resources and setting up IT systems capable of Fashion & Apparel MRP and production management.

Set up warehouse for domestic production Next, identify the warehouse that will serve the contractors’ and factories’ material requirements. The warehouse has to be located nearby to ensure faster material issuance lead times. Warehouse managers need to allocate floor space and implement efficient material receiving, put-away, picking, and shipping processes. Implementing a digital warehouse management system (WMS) capable of materials management is a must.

Establish CoE steering committee Collaborating between different departments to achieve the eventual goal of timely, cost efficient products loved by consumers requires a concerted effort controlled by a steering committee of stakeholders from product design, production control, planning, material management, and logistics & distribution.

Establishing a Center of Excellence (CoE) steering committee brings your efforts together and keeps your teams focused on their shared objectives. It ensures smooth collaboration with contractors and factories, and allows merchandizers to lead product line success across all sales channels.

Expanding your production operations network isn’t just an onshoring effort to bring production back to domestic markets. It involves taking a fresh look at organizing new process models. Use self-service portals for partners to provide the following capabilities:

Sharing demand forecast insights

Visibility to new product lines

Collaborative sampling processes

Factory-driven material consumption reporting

Factory-driven progress reporting

Sharing estimated capacity requirements for in-season replenishments

To minimize operational costs and maximize ROI, the CoE steering committee should focus on establishing a digital workforce using intelligent/robotic process automation (RPA/IPA). Here are some process areas they could focus on:

Work order issuance

Vendor invoicing

Contractor and vendor onboarding

Material issuance and allocation

Material consumption journal entries

Work order progress reporting

Material reorders

HauteLogic by Visionet Systems is a comprehensive, ready-to-deploy fashion solution for collaborative domestic Fashion & Apparel sourcing management, with self-service portals for contractors and factories and complete MRP and production control processes that are fully integrated with WMS and retail POS operations. Visionet and HauteLogic provide a full scope of services for establishing a digital workforce by effectively implementing RPA/IPA to enhance Fashion & Apparel operations.

When your retail strategy empowers employees through data and analytics, you enhance every aspect of their workday, which in turn leads to a better customer experience.

Enabling these enhancements requires a data management solution that is effective, efficient, and in a form that can be accessed quickly and easily by key employees in your retail business. Such data accessibility can be profitable, too – the global retail industry stands to gain an additional $94B in revenue over four years by taking full advantage of their data[1].

In this post, we’ll look at several major data management considerations for retail, including the key differences between ERP and EAI, choosing the right ERP, and a brief look at business intelligence.

ERP & EAI

Enterprise Resource Planning (ERP) and Enterprise Application Integration (EAI) are two popular solutions to data management woes, but in very different ways. For many large retailers, the question isn’t which of these two solutions they should use, but rather how to implement both of them most effectively.

An ERP platform is a single software application that integrates major business functions that span across core operations. This is where the collection and organization of all your data occurs. EAI, on the other hand, is a framework that takes multiple platforms and allows them to communicate, integrating the data between these different information systems that would otherwise be isolated in “data silos”. One important benefit of EAI, in addition to the core importance of communicating data, is that it allows companies to make the most of their pre-existing IT investments – a huge initial cost-saving measure.

Fear of disruption?

Sometimes companies are hesitant to implement these two very powerful solutions because of the risk of data loss or disruption. These risks can be avoided by choosing the right partner for your implementation efforts and having them available for employee support before, during, and after the implementation. Though it may seem obvious, having a clear idea from the beginning (and sticking to it) will prevent hours of headaches down the line.

One major prerequisite for successful implementing ERP and EAI is selecting the right ERP platform for your industry – one that can help you from a general operational standpoint by providing the tools you need to face problems specific to your line of business. For retailers, some examples of features that should come standard include:

POS management

E-commerce utilities such as destination-based taxation and real-time inventory updates

Contact center capabilities

Marketing - content and campaign management

Social monitoring

Store operations - statement reconciliation and pricing management

Supply chain and logistics

Sales force automation

Financial management

HR - payroll and related tasks

Business intelligence (BI)

Working together, these functions are essential for any retail business looking to create a memorable shopping experience that attracts loyal and engaged customers.

Making Data Usable

Having all the data in the world is useless if it doesn’t produce actionable results. BI is the process of taking raw data, giving it context, and arriving at one version of truth – and doing it an understandable way using a real-time “dashboard” that contains visualizations, graphs, and charts.

For retail analytics, BI can be integral in a number of ways, especially in customer investigation that helps enhance the buying experience. It can also be used to understand the relationship between purchasing patterns and other essential measurements across geographical locations. As BI is an ongoing process, particularly with regards to data updates within an enterprise data warehouse, having the right ongoing support from consultants can completely change your employee experience.

Conclusion

Better customer data management leads to a better customer experience and can have a positive impact that is felt tenfold across your entire business. So transitioning to a solution that enhances data management is well worth the necessary time and effort. Don’t let concerns about disruption keep your business from making this very essential transition, since deciding to wait will only lead to an increasingly complicated environment in the future.

One thing that every fashion and apparel business has in common is supply chain partners. Whether you’re an apparel manufacturer, retailer, or wholesaler, you’ll be communicating with a third party at some point in your supply chain.

This means that any hiccup in your communication cycle can hamper the overall delivery chain and may result in unhappy customers. No matter where you’re located, what fashion product you’re selling, or where you’re sourcing your raw material from, if you don’t have the right supply chain collaboration mechanisms in place, you can’t achieve sustainable business growth.

So where does supply chain unreliability come from, and what can you do about it?

Apparel Supply Chain Challenges

There are three primary factors that contribute to supply chain uncertainty:

Longer lead times for imported materials

As the number of well-informed and tech-savvy consumers increases, there is a proportionately higher risk of brand sensitivity. Any stock-outs or quality issues can divert your customers to competing brands that have a more responsive value chain. In other words, since full packed sourcing companies are completely reliant on vendors for the timely delivery of imported materials from multiple vendors to start the production process, the lack of a powerful vendor communication platform can result in longer lead times and put a strain on resources.

Tight delivery schedules due to seasonality

The fashion and apparel industry is replete with seasonal volatility due to holiday shopping, promotions, and sales. While this provides opportunities to attract high order volumes, mismanagement and lack of planning can have a negative impact on brand image and lead to permanent loss of sales. This creates a need for a flexible tool that offers more than just basic collaboration with vendors. It must provide near-instant response times and a complete view of all key performance indicators.

Inability to accurately estimate customer demand

Failure to predict what will sell the most, identify items that will soon go out of fashion, or discover new and lucrative consumer segments can cause companies to over-source materials that might not translate into sales, or under-source materials for products that may be in high demand. Organizations that base their estimates on guesswork instead of using data and technology expose themselves to profit erosion.

3 Ways to Reinforce Reliability

You can tackle these challenges by implementing a fully connected and integrated vendor collaboration structure across the following supply chain segments:

Production Planning

Using advanced analytics to project production plans according to consumer demand and identifying production issues earlier in the cycle through a well-connected business ecosystem will provide visibility to all of your vendors. This will help them plan for fallback material in advance and align on quick deliveries during highly volatile periods.

Seamless Order Issuance

Reduce steps from receiving production estimates to placing purchase requests, tracking orders, and clearing invoices by making sure that all data is aggregated in one place and is transparent to all third parties. You can accomplish this by reducing communication via email and auto-syncing business activities between your vendors’ systems and your own. This will reinforce proactivity and reduce last-minute deliveries and fulfilments, because all of your orders will be accurately placed in the right quantities with the right vendors at the right time.

Milestone Tracking

By bridging the gap between obtaining each order status from your internal supply chain department and following up with different vendors, advanced vendor collaboration technologies offer your organization the ability to track deep vendor milestones with automated notifications for any anticipated delays in predefined timeframes.

Your apparel firm needs more than just basic collaboration tools to gain the exceptional agility and market response time required in this industry. Join our experts at Visionet for an insightful webinar and learn more about how your fashion and apparel brand can maintain closer collaboration with vendors throughout the production and delivery cycle.

Wed, Aug 15, 2018 2:00 PM – 3:00 PM EDT

Microsoft Dynamics AX 2009 is 10 years old and mainstream support has already ended. Microsoft Dynamics 2012 has some years to go, but are you going to wait that long? In this webinar, ERP experts at Visionet will discuss:

How to avoid the risk of business downtime and achieve consolidation of CRM and ERP applications and infrastructure

How to enable digital transformation and create engaging customer experiences, optimize operations, and empower employees

Key components of a modern ERP

Top considerations when looking for a platform upgrade partner.

Online retailers face more competition than ever from the multitude of online competitors vying for a share of each customer’s wallet. With so many options so readily available, the convenience that online shoppers enjoy has become a challenge for retailers – the customer’s “switching cost” has become nonexistent. In other words, when every online store is just a click away, they all become interchangeable in the eyes of the customer.

This has caused retail models of the past to evaporate, and successful retail brands are constantly on the lookout for new ways to differentiate themselves from their competition. One way that successful retailers accomplish this is by tailoring their brand’s touchpoints to the tastes and preferences of their ideal audience.

Identifying your ideal customer personas is an important part of any modern retail strategy. It provides some important insights into the types of people who would be interested in buying your product. Taken on its own, however, simply knowing who to market your products to doesn’t provide a complete answer… it doesn’t provide much information on how these personas reach the decision to buy your product. For that, you need to map your customer journey.

In the same way that buyer personas provide an in-depth understanding of each type of potential customer, a customer journey provides a comprehensive map of the branching decisions that people make over the entire length of the customer lifecycle. Since different customer personas shop and browse differently, each customer’s journey will be different.

A complete customer journey begins with the customer’s initial interest in an item or contact with your brand, includes every touchpoint they could encounter decision pathway they could take, and extends beyond the actual product purchase, because delivery, after-sales service, and organic, word-of-mouth product endorsement are all important parts of the customer experience. Knowing the subtle ways in which shoppers meander through your world is crucial to reaching as many potential customers as possible and making the most of each touchpoint.

Creating a complete map of your user journey forces you to carefully consider each potential customer interaction, both deliberate and unplanned, and ask yourself what you can do to maximize the chances of guiding people closer and closer to conversion. As for customers that have completed their purchase, your goal changes to ensuring complete satisfaction, loyalty, and repeat business.

While you won’t find a single, one-size-fits-all solution that applies to all businesses (or even all products sold by the same business), the best way to map your customer journey is to ask what it would take at each touchpoint to convince a shopper to proceed to the next phase. The answer to this series of questions will give your brand’s user experience (UX) a clear and well-defined direction.

Visionet’s UX experts help map your organization’s customer journey to identify and create optimal customer experiences that enable you to meet aggressive revenue goals across digital channels. Our creative team provides expertise in UX, information architecture, and creative design that optimize your brand’s digital customer experience.

When combined with our eCommerce technology, digital strategy, and digital marketing services, Visionet UX can help you revitalize each facet of your global brand’s digital footprint. Please contact Visionet Systems to learn more.

Retail Automation is the latest development that intends to bring a revolutionary change in the global retail market. Retail Automation provides a tool which handles all retail relating activities such as product handling, time & attendance, workforce management, task management, store audit helping the retail owner to increase the work and store productivity.

Demand Scenario

The Global Retail Automation Market was 10.31 Billion USD in 2017 and is estimated to reach 18.76 Billion USD by 2023 with a CAGR of 10.49% during the period.

Growth by Region

North America will lead the market with a 45% market share in 2017 followed by Europe, Asia-Pacific. The growth in the North America region is due to factors such as growing demand for efficient retail services, need for time reduction, increased accuracy and high living standards.

Drivers Vs. Constraints

As there are huge opportunities in development of retail automation systems, there is an increase in usage of smart phones and enhanced internet accessibility, this in turn drives the growth of Global Retail Automation Market. Increased adoption of automation technology by end users such as supermarkets, hypermarkets, fuel stations and pharmacy stores, paves the way for growth of this market.

Industry Structure and Updates

In January 2018, Toshiba unveiled their innovation which is used to deliver enhanced customer experience in retail industry, which is expected to increase the sales of company exponentially.

At National Retail Federation 2018, Datalogic announced their new technology in retail industry which is intended to attract customers and increase their sales.

Visionet Systems, Inc., a leading technology solution company, announced today the launch of HauteLogic, a complete cloud-based business management solution for fashion and apparel industry that covers wholesale, online retail, brick and mortar retail, and apparel manufacturing. HauteLogic – Fashion Delivered Right, brings digital transformation to the doorstep of the fashion and apparel industry to manage every aspect including planning, design, production, and distribution processes, to help brands establish and maintain market leadership in the fashion industry and future-proof their investments. Built using Microsoft’s advanced disruptive technologies, it enables superior workflows across both internally to empower employees and workers, and externally to provide high-quality customer experiences throughout the engagement cycle.

HauteLogic is a comprehensive industry solution that addresses the needs of fashion businesses of all kinds. A ready-to-adopt solution built on the Microsoft Dynamics 365 cloud ERP platform, which uses integrated machine learning, advanced analytics, partner communication, and eCommerce functionality. HauteLogic simplifies the supply chain with vendor collaboration, integrated merchandising, and intelligent shipping. It integrates out-of-the-box with leading e-commerce platforms for easy omnichannel enablement and provides inventory optimization capabilities powered by AI. HauteLogic extends Dynamics 365 production control functionality to accommodate most flexible, responsive and scalable in-house or outsourced apparel manufacturing processes for fashion companies. In an industry where creating exceptional customer experience is essential to building brand loyalty, and lowering design to shelf time is critical, HauteLogic is the answer.

Highlights:

The single End-to-End system to manage all aspects of your business, bringing process + people + data together.

Modular design which will help business leaders grow their business (wholesale to direct-to-consumer to vertically integrated global retail)

Hundred plus pre-configured fashion related processes built on industry best practices

Significantly reduces the implementation complexity and time commitment

Embedded analytics for real-time operational visibility to management

“We are very excited to deliver our revolutionary omnichannel solution to the Fashion and Apparel world providing them the flexibility required to scale up their business,” said Jawad Khan, EVP at Visionet. “We believe that HauteLogic’s advanced, unified, and modular functionality will deliver efficiency and long-term value to fashion brands that manufacture, distribute, and sell apparel, footwear, and accessories. Organizations can implement the parts of HauteLogic that make the most sense for their operational model and conveniently add other components as they evolve and expand. Visionet has leveraged its twenty-plus years of fashion and apparel industry experience for developing the HauteLogic solution, which will allow businesses to enhance and optimize every aspect of their operations.”

HauteLogic (SCM) along with Visionet’s other solutions like CommerceLink, PartnerLink, AcuitySpark, and Advanced Shipping are all available on the Microsoft Appsource – the premier destination for Microsoft approved business apps. These solutions will also be showcased at the Microsoft Premier Partner Event “Inspire,” to be held in Las Vegas July 15th-19th.

Customers have become increasingly responsive to new trends and their range of preferences have also diversified, leading to an explosion in the variety of products being sold. High demand for product variety, especially in the case of short lifecycle products like food, apparel, toys, and computers, makes it challenging for manufacturers and retailers to forecast which precise range of products will be a hit with consumers. Extreme competition in the marketplace has forced companies to respond more quickly to customer needs through faster product development and accelerated delivery schedules. Only those companies that offer highly relevant products and deliver them on time receive their customers’ full support and appreciation. Manufacturers and retailers must join forces across the supply chain to become more effective in aligning supply with actual consumer demand.

Improving collaboration, agility, and visibility are the three most important ways to strengthen your supply chain. Each of these three attributes offers multiple operational enhancements for manufacturers and retailers in the fashion, apparel, and consumer goods industries.

Collaboration

Through collaboration, manufacturers and retailers can meet customer demand better by sharing sales information amongst themselves to generate accurate demand forecasts. Sharing information up the supply chain can help companies proactively adjust to evolving supply demands, which leads to less on-hand inventory. Not only is continued collaboration with dedicated partners the best way to reduce long-term supply chain costs, but it also leads to developments in product and process innovation. Instead of relying on telephone conversations or email, leading enterprises use modern communication solutions that seamlessly transfer relevant business information between trading partners’ enterprise systems. Using a specialized business communication solution based on electronic data interchange (EDI) or more modern direct-B2B technology is a great way to ensure secure, reliable, and efficient partner communication.

Agility

High agility enables your business to identify and respond to disruptions to ensure quality customer service. With complete operational integration from manufacturing to delivery, an agile supply chain can adapt to virtually any situation, from vendor reliability issues to unexpected spikes in demand.

Real-time demand data and accurate forecasting make your workflow and production volume more flexible and contribute to greater business output agility. In-depth business intelligence tools can keep track of this information and analysis, and share it with relevant stakeholders across your entire supply chain. More advanced BI tools will notify you if specific performance metrics exceed predefined thresholds that indicate the need for your immediate attention, and cutting-edge solutions use machine learning and heuristics to identify problematic situations, even if they’ve never been encountered before. Techniques like robotic process automation (RPA) and intelligent process automation (IPA) can improve agility even further by initiating corrective actions whenever specific events occur. This allows your business to continue operating according to changes in demand, supply, and other market trends, even when human decision makers are not immediately available.

Visibility

Real-time visibility across the entire enterprise is absolutely crucial for informed decision making, order tracking, and inventory management. When new trends emerge in customer or production data, it is important for this information to be in the hands of people that can make value-enhancing business decisions. Organizations with total supply chain visibility don’t measure business through operational silos, with each department or business function operating in isolation. Instead, they take a cross-functional approach that provides an integrated view and allows decision makers to gauge overall performance. Having a fully integrated solution enables the system to seamlessly pull in information from across the enterprise, including production, warehouse, delivery, and sales.

Fully-integrated ERP solutions can help you enhance your organization’s collaboration, agility, and visibility by unifying all supply chain business functions in an easy-to-manage, reliable, and adaptive manner. To learn more about how to leverage digital technology to reduce complexity and improve communication across the supply chain, join supply chain experts at Visionet Systems on July 26 for a webinar on “Improving Supply Chain Reliability with Deeper Vendor Collaboration”.

Enterprises large and small need to use all means at their disposal to gain a strategic advantage for their business. To remain competitive, these organizations must make use of contemporary machine learning tools to unlock value and meaning from the wealth of data they have about their customers, products, employees, work processes, and even competitors. Whether their customer service department wants to look at how their customers feel about their products, or their sales and product design teams need to analyze what products would sell when, to whom, with what features, and at what price point, advances in machine learning can enhance existing data models and take this decision making to the next level.

So, what do businesses need to unlock the value in their data? After all, most machine learning tools are open source and there are plenty of commercial machine learning platforms that promise to run a number of models on your data. Then why is it so hard to adopt machine learning?

It’s a numbers game

As is so often the case, the answer lies in numbers. Machine learning algorithms crunch numbers, so the transactional and analytical data that enterprises have in their databases and data warehouses needs to be selected and prepared to be fed into these algorithms. There are several data preprocessing steps, from data imputation that addresses data sparseness to techniques for normalizing and standardizing data, allowing the appropriate machine learning model to be applied.

Data Imputation and Normalization

Common techniques for data imputation provide default values, such as 0 where none exist, or correct for erroneous and outlier data, thereby reducing “data noise”. The process of standardization and normalization utilizes a number of techniques for data preparation based on the type of machine learning model that needs to be utilized for a given business problem or question, such as label encoding and one-hot encoding to transform textual data values into an appropriate set of numeric values that do not introduce artificial correlation within the data.

Data Reduction

Other data normalization techniques involve reducing the amount of data that needs to be presented to the machine learning model so that the models can efficiently process the data and, more importantly, only consider the data that falls within the business domain of the question or problem being solved. Common data reduction techniques involve reducing dimensionality by creating composite dimensions and by feature engineering, which looks at statistical characteristics of the data like standard deviation, entropy, and correlation to identify the set of data fields that are important for the machine learning model to consider.

The value of skilled data scientists

Popular data scientist surveys indicate that all of this preparation constitutes about 70 to 80 percent of the work that goes into developing and running machine learning models. Once the preparation is done, machine learning models can discover myriads of data permutations and combinations that contribute to the answer the business is looking for.

All of this work requires a trained data scientist with a keen understanding of statistical and mathematical data manipulation techniques, technical skills in data processing tools like Python, R, sklearn, and pandas libraries, and in case of big data tools like Apache Spark, the ability to quickly prepare the data set and select relevant machine learning models for enterprise data. Visionet's advanced analytics team is well-versed in these data processing and analysis tools, offers strategic advice to its customers on setting up their machine learning-based analytics programs, and provides a deep bench of onshore and offshore data scientists to do all the preparatory work in an efficient and cost-effective manner.

When you mention robots, most people think of Star Wars or those car-manufacturing assembly lines where giant, agile machines move heavy parts, make spot welds or secure bolt-on chassis. Robots have developed to the point where robotic process automation (RPA) is now coming to the world of corporate finance.

In finance, we’ve automated by implementing general ledger and enterprise resource planning (ERP) systems, as well as spreadsheet programs like Microsoft Excel. Yet many corporate financial processes are still stuck in the 20th century. Corporate finance teams spend about 80%of their time manually gathering, verifying and consolidating data, leaving only about 20% for higher-level tasks like analysis and decision making.

RPA will unleash a new wave of digital transformation in corporate finance. Instead of programming software to perform certain tasks automatically, RPA uses artificial intelligence (AI) to train and teach software robots to process transactions, monitor compliance and audit processes automatically. Machine learning, a form of AI, takes finance automation even further -- by building systems that have the ability to automatically learn and improve based upon new data and experience -- without being specifically programmed to do so.

According to a recent survey by Grant Thornton (paywall), corporate finance executives are embracing these new forms of finance automation, ranking AI and advanced analytics among their highest-priority planned investments, while many have already begun their digital transformations.

In the area of transaction processing, CFOs can use forms of RPA to optimize their accounts-payable and accounts-receivable processes. How a corporation collects from customers influences both cash flow and customer satisfaction. A CFO’s company may already do that well, but AI augments such expertise so that the company can collect as expeditiously as possible while maintaining good customer relations.

At the same time, a customer may make a duplicate payment, combine multiple invoices into one payment or pay the wrong amount. Manually correcting the errors in the general ledger system can take an enormous amount of time to sift through invoices, find the source of the errors or track down the customer to get the problem resolved. AI and machine learning could support finance teams by automatically tracking down the relevant information, finding the source of a GL problem and suggesting which payments to match to which invoices.

AI can also mitigate financial risks by stopping erroneous payments to vendors in near real time. For example, enterprises with $500 million in annual payments could be leaking anywhere between $500,000 and $2.5 million in cash from errors, fraud and misuse. Today, large organizations rely on manual sample audits of invoices and payments to mitigate risks. However, these sample audits encompass only a small fraction of transactions, thus finding little in the way of errors or waste in the process. However, AI can expand the scope of compliance monitoring and analysis, saving millions and preventing duplicate and fraudulent payments while stemming the tide of cash leakage.

AI spots microtrends and uncovers problems that humans often overlook. It augments what humans do and enhances their effectiveness, speed and efficiency. It’s similar to the revolution we’ve seen in manufacturing robots because the combination of automation and artificial intelligence in accounting is faster and more reliable than humans alone.

However, RPA doesn’t just automate operations -- it allows you to redesign and improve processes and even help educate humans about better ways to work more efficiently and make spending decisions.

For example, say you have an account executive who travels to New York City. It’s December -- the most expensive time of the year to visit New York -- and your executive spends $500 a night for her hotel room. That’s what you’d expect to pay for a hotel around Christmas. The AI-based system wouldn’t flag that trip as an anomaly.

But say your AE travels to New York a few months later, when hotel rates are typically lower, and again pays $500 a night. Armed with data from millions of expense reports, an AI system would know that this rate is extravagant for a trip to New York in March, flagging the transaction and informing her that the going rate for a quality hotel in Manhattan should be lower. The result is that in the future, the executive makes a better decision about where to stay and how much to spend. In this way, artificial intelligence steps in with the guidance an account executive needs to do her job faster and more efficiently, reducing risks and saving her company money.

In this way, AI can help teach employees to see patterns they’re not aware of and to understand the implications of their behaviors and transactions, so they make better financial decisions in the future.

Helping CFOs Get The Job Done

Company executives, too, can use AI to identify opportunities to improve company policies and procedures and to make better financial decisions. Forms of AI such as voice-enabled digital assistants like Siri and Alexa are now widely used by consumers. These devices are likely to find their way into corporate boardrooms and executive suites -- or even cubicles -- in the future. For example, CFOs could use digital assistants to access data analytics systems and instantly answer questions on the fly to drive strategy and decision making in a corporate board meeting and beyond. Just as software robots get smarter over time, AI technologies could also end up helping humans make more informed decisions and even get smarter, too.

AI isn’t a moon shot for your company. Thanks to increased computing power and improved machine learning algorithms, AI is becoming a reality for corporate finance teams, moving beyond “Do I need to take this risk?” to the point where the greatest risk is in not adopting AI -- because your competitors already have or soon will.

Webinar starting Time: Thu, Jul 26, 2018 1:00 PM - 2:00 PM EDT

Reliability is the most critical performance indicator for fashion and apparel manufacturers and retailers leveraging full packed sourcing models, as they face longer lead times for imports and tight schedules for typical season deliveries. Lacking the responsiveness and flexibility required to intelligently manage domestic outsourcing operations and shop floors, manufacturers today are exposed to a risk of falling behind in the race of competing vendor margins and a differentiated customer service. In this webinar, fashion and apparel supply chain experts at Visionet will explore:

How fashion and apparel brands can ensure better collaboration with vendors throughout the production planning, order issuance, and tracking cycle

How to manage individual milestones, and identify and address production issues and delivery risks in a timely and efficient manner

A live demo of Visionet’s intuitive HauteLogic solution that unifies vendor collaboration, order management, approval workflows, and milestone tracking and monitoring

Once it becomes clear that your business requires an ERP solution to make its next leap forward, your real implementation challenges begin. You need a thorough plan to ensure that the implementation phase is as short and pain-free as possible – a plan that considers all current and future business objectives that the ERP system needs to address, as well as any challenges that apply specifically to your line of work. ERP implementation is a complex process, and missteps are easy to make, unless your plan is airtight.

Here are 5 best practices that will make your life easier during this challenging process. Keep them in mind, and you’ll be enjoying the benefits of ERP technology in no time.

Understand ERP benefits for specific business processes to secure executive buy-in. While the myriad benefits of ERP solutions might be obvious to you, other decision makers and stakeholders in your organization might require some convincing. Getting decision makers on board is essential, since 46% of CIOs surveyed claimed that the business case for ERP implementation was “not compelling” enough. Here’s one powerful way to help your ERP implementation project gain traction: make a list of specific challenges your organization is currently facing, or business processes that aren’t as efficient as they should be, and then match these opportunities for improvement with the particular changes that an ERP system will make to address each one. This will help you secure buy-in from your company’s executives by demonstrating real, measurable value.

Select an ERP solution that addresses your industry needs. Choosing the right ERP system helps improve ROI, which greatly improves the odds of securing executive buy-in for such a major change. That’s why you should determine whether your business can benefit from industry-specific ERP solutions. ERP platforms that are more closely aligned with your business processes take less time to implement because they require less customization. The more comprehensive your implementation plan is, the easier it will be to choose the right ERP solution. Your final ERP implementation will also be better-equipped to perform tasks the way they are expected to be done in your industry.

Plan for every contingency. As mentioned above, ERP implementation tends to be complex, and extenuating circumstances can arise. Having a contingency plan for each possible challenge can save you a great deal of time, effort, and money. From data cleansing and migration to user acceptance and regulatory compliance, it helps to factor in all possible sources of risk and devise strategies for mitigation. Your data will remain accessible, and your workforce will continue to perform close to peak productivity during the transition.

Consider the need for workforce reallocation. Since ERP systems improve operational efficiency, it is natural for job responsibilities to change somewhat. During the implementation phase, workers that have prior experience with technology rollouts of this kind can be valuable assets, and might be better-suited than their coworkers as liaisons with your ERP implementation partner. After the implementation is complete, workers that used to perform a single manual task might find themselves verifying the results of several ERP-automated processes. Workers that were once stuck with boring, repetitive duties often find their time freed up for more creative or customer-oriented responsibilities that require a human touch that ERP systems can’t provide.

Invest in training and change management. According to 82% of CIO respondents, one of the biggest barriers to implementation is the resistance to change. Some team members are bound to hesitate when asked to start using a new ERP system, and might also be unaccustomed to the degree of tracking and visibility that ERP solutions provide. Keeping employees engaged and soliciting their feedback is critical for quick and painless user adoption. To dispel feelings of anxiety, it helps to generate excitement around the shift by highlighting the positives associated with ERP systems, such as automation of repetitive processes or better data availability.

Your employees will also require initial and ongoing training and support to ensure that all personnel are comfortable with the system and prepared to get the most out of using it. Your ERP implementation partner is an indispensable resource in this regard that can help your employees quickly acclimate to the new ERP platform. Use regularly scheduled meetings with your implementation partner to quickly address training-related challenges, some of which might indicate a gap between the ERP system’s capabilities and user expectations.

Conclusion

Successful ERP implementation relies on understanding your needs and setting expectations, choosing the right solution, thoroughly planning for contingencies, appropriately allocating resources, and preparing your workforce for the road ahead. By paying attention to these five essential aspects, your ERP solution will take less time and investment to roll out, will offer functionality that works better for your business, and will quickly gain support from all levels in your organization.

“AI is the new electricity” 

said Andrew Ng

Artificial intelligence (AI) has indeed come a long way from being confined in the research laboratories or science fiction movies. It is a persistent reality in today’s world, which has permeated every layer of business, causing disruptions of unprecedented magnitude.

In such a short span of time, AI has an incredible impact in reshaping the entire retail landscape by boosting productivity, increasing accuracy and improving reliability of business intelligence.

AI and machine learning have already begun to make sweeping changes to the entire retail ecosystem. Spread across the supply chain, customer acquisition, shopping experience, purchase pattern analysis, and customer retention and loyalty, the value that AI brings to each aspect of retail is both intensive and revenue-boosting.  

Consumers today are more self-aware, and demanding than any generation ever before. It is about “I want what I want when I want it”, which stands for personalized, targeted, omnichannel, ever-present market place enabled by the Internet. Businesses that understand this new paradigm and deliver, are the ones that are going to win.

By increasing customer awareness of a brand, and informing the brand about its customer personalities and behaviours at a granular level, AI enables fulfilment of customer desires by accurately analysing consumer behaviour. AI helps engage consumers by producing targeted content and curated lists, which all help sell well, faster, and in bigger volumes to improve the bottom line.

Traditionally, AI has been applied in retail in the realms of customer segmentation, inventory management, recommendations, campaign management and in creating insights. The evolved AI of today helps retail companies in doing much more such as enhancing inventory management, enhancing targeted recommendations, and keep churning out sticky content that makes customers visit, and eventually, buy.

In ecommerce, techniques such as collaborative filtering are employed to tailor recommendations based on personalities, item-item similarity, grouping, and targeted shopping deals. AI also adapts to provide recommendations that suit seasonality and business verticals, to provide the user just what he/she needs before even one asks for it. Such effective engagement directly translates to more sales.

Predictive analytics of consumer behaviour helps determine inventory better, and dynamically deploy vouchers, coupons and discounts to maximise engagement. Doing it all is an intelligent system that crunches data in huge volumes, and helps retailers makes sense of it by providing actionable intelligence.

AI also helps in the efficient management of inventory, with evolved logistics that stocks by predicting customer behaviour, and also in the application of drones and other better material handling systems that create a fluid and fast process from click to delivery.

Retailers can now access deeper insights about their customers with a click of a button on an easy dashboard. Such data-backed understanding helps retail companies hyper personalize shopping experiences to unprecedented levels. Customers of today, especially millennials (aged 35 and younger) grew up with the Internet, and are much more aware than the previous generations.

By default, they expect their retail shopping experience to be highly personalized, where every inch of screen space is expected to be tailor fit to reflect even the smallest detail of one’s personality and buying power.

Thanks to what is called the ‘phygital’ retail – where brick-and-mortal stores can be infused with digital capabilities. In omnichannel retail, where buying points are diverse and inclusive, AI is expected to straddle such spaces, and make retail a much more targeted, immersive, and pleasantly-personalized experience in the near future. Wold over, such omnichannel approach that offers such smart and seamless shopping experiences for customers has begun to appears a norm than an innovation.

Behind the flashy screens, lie the ability of AI evolution in the areas of vision, speech and neuro linguistic programming (NLP – that helps understand the deeper motives of the subconscious mind by studying human behaviour).

Such evolved technologies fuelled by sheer computing power help fruitful use-case analysis, and better engagement of the customer by helping him/her shop not just more, but better and faster. Applying this omni-channel capability, retail companies can transform most just their online operations, but physical stores as well.

While extensive application of AI in all aspects of retail across the world is still in its infancy, it is expected to evolve faster than we think, thanks to its very nature: Continuous self-learning to make processes better. The rise of AI is also not expected to limit itself to e-commerce. We can expect new surprises in every business realm, where AI would be the enabler behind the screens.

Retailers that don’t carry enough inventory suffer from low sales revenue, while retailers with too much stock suffer from too much overhead. Both types of miscalculation take a heavy toll on profits, which means that prompt and accurate tracking, reporting, and forecasting of consumer demand is critical for retail success.

ERP solutions track transaction information across retail channels in real time, instantly generate and deliver reports and performance metrics, and intelligently forecast future demand curves with unsurpassed agility. After implementing an ERP platform, decision makers in your retail business will gain a much richer understanding of how effectively each department and business unit in your organization contributes to order fulfilment and customer service, both individually and in coordination with each other.

ERP systems enhance all three of these critical processes: tracking, reporting, and forecasting. This post considers how ERP solutions augment each of these processes.

Tracking

From financial management and accounting to human resources, payroll, and employee scheduling, every aspect of your retail business is important. With an ERP solution, retailers can easily keep track of not just their sales transactions and stock levels, but every aspect of their business operations.

ERP systems track several crucial retail processes, including:

Sales transactions across all physical and digital retail channels

Order fulfilment, including cross-channel fulfilment and delivery tracking

Customer interaction via social media, customer service, etc.

The effect of promotions, advertising, and marketing campaigns

Supply chain and distribution costs, replenishment schedules, etc.

Retailers can have their ERP deployment customized even further to track specific activities, variables, and KPIs that are relevant to their particular line of business (apparel & footwear, consumer goods, etc.). Industry-focused deployments of this kind keep track of metrics and relationships using terminology that’s specific to your trade.

Reporting

On its own, tracking information doesn’t offer much value. After it has been collected, your business data needs to be converted into clear, actionable information. Business intelligence (BI) solutions facilitate informed decision making and give context to your unstructured data. ERP and BI capabilities work in tandem: your BI software analyzes data from your ERP system and presents this single version of the truth as easy-to-understand performance metrics and reports.

Some retail businesses make the mistake of skipping BI integration as a cost-cutting measure, because they think BI is an optional activity. This is certainly not the case, and BI should be a core component in your ERP implementation from day one. Better planning is a primary motivating factor behind implementing an ERP solution. After all, that’s what the “P” stands for!

Forecasting

Tracking information is necessary for generating business reports, and reporting is indispensable for understanding how well your business is performing. However the most successful retail brands understand the limitations of descriptive reports, and insist on analytical tools that can generate projections and perform advanced forecasting. Without such forward-looking analytics, organizations remain firmly entrenched in a passive mode of thinking, and often fail to react to emerging trends in time to capitalize on important opportunities.

BI-enhanced ERP systems use real-time data to automatically perform accurate predictive analyses. Some advanced ERP platforms are even capable of autonomous decision making, and can be authorized to make some choices based on this forecasting without requiring any human intervention. Sometimes a machine that isn’t susceptible to human biases is better for making impartial decisions based on pure quantitative analysis.

Together, ERP and BI can track and anticipate issues brewing on the horizon, like supplier shortages. Your ERP system tracks each supplier’s consistency in pricing and quality in real time. As soon as it detects significant changes in a vendor’s behavior, your BI solution will raise a red flag, allowing you to make any necessary procurement changes before you encounter inventory shortages.

Conclusion

The right ERP solution for retailers adds BI capabilities to its core ERP platform, delivering actionable insights, reports, and predictive analyses that you can use to make informed, data-driven decisions.