Blog Archives | Quantzig

Myth Busting: Everything You Need to Know About Multi-Channel Marketing Attribution | Quantzig

The rise in popularity of digital media channels and platforms, along with the importance placed on customer-centricity, has resulted in high demand for more accurate methods of measuring marketing ROI across industries. Marketing attribution or multi channel marketing attribution is not a new concept, and some early adopters in the business world have used different versions of this model. However, the influx of massive data sets from various sources like social media, websites, and other digital platforms have given rise to the adoption of multi channel marketing attribution models.

In this article, Quantzig aims to dispel some common myths around multi channel marketing attribution, shedding light on how marketing attribution works and empower brands to develop and deploy their own programs to gauge ROI and performance.

Partnering with us to devise a multi channel attribution model for your organization helps you adopt a progressive approach with continuous guidance and support from experts to guarantee the basic adequacy of the model. Request a FREE proposal to get started.

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#1 Multichannel marketing attribution only benefits B2C companies

For years now, multi channel marketing attribution was only associated with B2C firms and their campaigns aimed at retaining customers. Though B2B businesses have been slow to realize its true potential, almost all leading B2B companies today have incorporated multi touch marketing attribution into their marketing models. And despite facing greater challenges when compared to B2C companies, B2B companies are placing no less importance on attribution. In fact, justifying marketing costs and calculating ROI was a major challenge faced by B2B business leaders globally.

#2 Multi channel marketing attribution models are static

It is a well-known fact that multi channel attribution modeling can be complicated and confusing for those who do not possess the necessary skills and capabilities to understand its intricacies. Though there are a wide variety of models available today, its quite impossible to find one that is pre-aligned with your business objectives. Irrespective of how simple or demanding the process of establishing an attribution model is, businesses should continually refine their approaches and measure the shifts based on channel performance and brand affinity. Adopting a standardized approach or a static model may lock in incorrect assumptions about the customer journey resulting in inaccurate ROI findings.

Analyzing huge volumes of customer data generated from several touchpoints is quite a big challenge. Speak to an expert to learn how we can help you tackle this challenge.

#3 A multi channel marketing attribution model is a necessity

The benefits of deploying a multi channel marketing model can be far-reaching due to its ability to help track user journeys and account for consumer activity in several ways. But the ability to analyze data, as well as translate them into tangible insights that closely relate to ROI, is where the real challenge lies.

For businesses, multi touch marketing attribution is a moving target that often changes faster than the business cycle. While not every company will be inclined towards making such huge investments, having realized its benefits, many have moved towards that direction.

Notably, companies that are well-equipped and take the necessary actions to develop and implement an attribution model have been successful in turning the benefits of attribution into a key differentiator. Our cross-functional teams comprising of 550+ data scientists and data analytics experts possess the domain expertise required to build systems that help correlate customer actions to financial outcomes.

When it comes to driving revenue through your marketing channels, it is crucial to ensure your marketing campaign aligns with customer acquisition strategies. Request for more information to gain comprehensive insights into our capabilities.

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5+ Reasons Why You Need a Data Warehouse to Manage Business Critical Data | Quantzig

Data that is generated and captured from various sources across an organization is one of the most valuable assets of the organization. But with data growing exponentially, businesses are often overwhelmed by its expanse and complexity. The best solution to tackle this concern is to gather, organize, and store all critical information in a common data warehouse.

Data warehousing and data mining as a technology framework was initially used to help business leaders better manage, comprehend, and capitalize on the data they possess. The traditional systems that collated data into a central, schema-driven repository for analytics and reporting worked exceptionally well for many years. Today, data is evolving at a pace that is rapidly transforming business processes, prompting decision-makers to adopt a novel approach to data warehousing business intelligence (BI).

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The traditional data warehousing system is witnessing a radical transformation due to the rising pressure from the influx of huge volumes of unstructured data, the rise in data formats, the real-time processing velocity, and the different ways businesses are using data. When compared to the modern data warehouse concepts, traditional data warehouse and data mining systems are different and often store data in the form of small data sets or tables. Notably, a significant benefit of a modern data warehouse over a traditional database management system is that it helps to integrate and analyze data from disparate sources when it comes to formulating detailed data reports.

Moreover, the modern enterprise data warehouse adopts a logical approach to scale insights and meet the demands in today’s data-intensive world. Hence, it could be said that a modern data warehouse and data mining system plays an active role in reducing the time and cost that is otherwise required to analyze critical data. As such, businesses end up saving time and resources that can be utilized for other priority functions.

Importance of Data Warehouse

A data warehousing system is a modern database management system that is commonly used by organizations for data research, conducting a prior investigation, demand forecasting, and trend analysis. The objective, however, revolves around the need to standardize and collate data from various sources into a unified platform. More importantly, a data analyst plays a crucial role when it comes to leveraging BI tools and the information in the data warehouse to create dashboards, reports, and monitor critical metrics.

Why do businesses need a data warehousing system? This question continues to haunt business leaders even today.

Here’s a simple answer- A data warehousing system plays a crucial role in data analysis because objectifying your BI measures without the application of insights from an enterprise data warehouse systems doesn’t ensure the stability or reliability of data in use.

Did you know? Data warehousing helps businesses to make better decisions at all levels within the organization and even across organizational boundaries. Contact an analytics expert to learn more about its benefits.

Benefits of Deploying a Data Warehousing System

For businesses, a common goal is to settle on better business choices using data-driven insights. A data warehouse, when integrated into your knowledge management process, can profit your organization in numerous ways like –

Deploying a modern data warehouse enhances BI capabilities

An autonomous data warehouse improves data quality and consistency

Data warehousing can improve the decision-making process

Improves the quality and accuracy of forecasts

Helps generate a high ROI

Streamlines information flow and knowledge management

Provides a competitive edge

Though its benefits are widespread, building a data warehousing system is not an easy task. Hence, we suggest adopting a progressive approach, along with guidance and support from data science experts to test and find loopholes to guarantee the basic adequacy of the data warehousing system.

To drive the best outcome, it is crucial to collaborate with an analytics firm that can help you in building your optimal data warehouse. Quantzig’s team of 550+ seasoned analytics experts and data science professionals have the expertise and skill it takes to design and build systems tailored to the particular needs of your business and equip you with data-driven, actionable insights for prudent decision-making.

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5 Steps to Supercharge Your Business by 10X Using Voice of Customer Analysis | Quantzig

To improve profitability, understanding the feedback of both current and potential customers expressed through all types of channels, and touchpoints is crucial from a business perspective. This is also why the voice of customer analysis initiatives of brands today encompass a new territory of unsolicited and unstructured data including comments on feedback forms and surveys, call center verbatims and social media engagements.

Though there exist several methods using which businesses can unearth valuable information to make customer-centric decisions, they must possess the basic capability to analyze the share of voice. Our customer analytics experts have listed few widely accepted methods that can help decipher the customer’s share of voice.

Feedback and survey analysis
Social media monitoring
Analysis of net promotion index

To succeed in today’s business world it’s crucial to identify customer needs and the issues that prevent your organization from catering to the needs of your customers. This article offers insights into the top five steps that will help supercharge business growth by 10X using VOC data.

Calculating share of voice is crucial as it helps analyze brand awareness and visibility, both of which are crucial to driving success in today’s competitive business world. Request a proposal to learn how we can help you gauge these metrics using an analytics-driven approach.

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Five Steps to Boost Growth Using Voice of Customer Analysis

Step 1: Gather customer data from various touchpoints

The first step in conducting the voice of customer analysis revolves around aligning strategies adopted to collate data with the end goals. Conducting a detailed assessment will help businesses to identify the best methods to capture data from various customer touchpoints. Once a holistic view of customer sentiments and feedback is established, businesses can then turn VoC data into actionable insights.

Step 2: Turn raw customer data into actionable insights

To comprehend the information encapsulated in large VoC data sets, you must first transform complex data into a condensed dataset that can be queried by analysts and consumed by sophisticated machine learning algorithms to deliver meaningful insights. As such, an essential phase in building a voice of customer analysis program will revolve around identifying customer sentiments at each stage.

Step 3: Analyze insights to understand customer needs

The use of advanced technologies, BI tools, real-time monitoring systems, and reporting dashboards can enhance the voice of customer analysis process, delivering much-needed customer insights. These insights, in turn, help determine common trends, pain points, and high-potential customer segments to devise suitable strategies to retain them by alleviating their problems.

Step 4: Leverage sentiment analysis to identify factors influencing customer feedback

Sentiment analysis helps analyze customer feedback to understand customer perceptions better. However, owing to the availability of huge troves of datasets, it isn’t enough to gain a holistic view of your brand’s perception in the global market. Performing a root cause analysis to analyze real-time VoC data and determine factors influencing customer feedback is the need of the hour. The insights gained can then be further leveraged to make decisions and implement new policies for product and service improvements.

Step 5: Devise a multichannel voice of customer analytics program

The successful implementation of a voice of customer analysis program revolves around converting data into accessible information. The use of customized dashboards to visualize VoC data and translate it into actionable insights can help them make crucial business decisions.

Did you know? Tuning in to the voice of customers helps unlock new performance improvement opportunities.

Contact an analytics expert for personalized insights on how voice of customer analysis can help your organization.

Why Quantzig?

In today’s digital era, data is ubiquitous, and the insights obtained from them are increasing and impacting the business world in innumerable ways. However, the real challenge lies in turning data into insights that help make crucial business decisions.

We, at Quantzig, firmly believe that the capabilities to act on insights obtained from the influx of continuous data is what drives an organization’s competitive readiness. Hence, our objective is to bring together the best combination of analytics tools and data-driven insights to help our clients build the necessary capabilities to build a detailed voice of customer analysis program. Having worked with leading brands across geographies, we have gained the domain expertise required to understand the unique challenges facing businesses. Collaborating with us can help you drive long term success by incorporating best practices and techniques that leverage advanced computing algorithms and data science to optimize, automate, and find value in data even in the most challenging situations.

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Quantzig Says Business Leaders Should Focus on Big Data and Knowledge Management to Bounce Back from the Crisis: Here’s Why

Businesses are fast transforming to adapt to the ongoing shifts in today’s dynamic business world. These shifts have transformed several business processes, generating huge troves of complex data sets that cannot be analyzed using the traditional rules-based data management systems. At the same time, the developments in artificial intelligence and database technology have brought the promises of big data and knowledge management back into the forefront. As such, digitalization driven by artificial intelligence, machine learning, deep learning, and cloud computing will have a profound effect on how businesses process data and share insights.

This article offers insights into the benefits of deploying a big data and knowledge management system and illustrates how it can impact outcomes in the new business era.

Leveraging big data to create business value is not new; however, the effective use of big data is now becoming a key differentiator. Request a proposal to glean insights into how we help our clients gain a competitive advantage.

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Analyzing the role of big data and knowledge management in the modern business era

A key factor defining success in today’s complex business scenario is the availability of relevant information at the right time, place, and in the right format. Moreover, businesses must know what decisions should be made, when to act on insights, and how these decisions will impact the business outcome. Notably, the growing demand for these insights has fueled the growth of big data and knowledge management systems across sectors, empowering businesses to make smarter decisions that can transform the way they handle their operations and compete in a rapidly evolving marketplace.

Besides, the convergence of data and analytics and the rise in processing power is helping businesses unlock the true potential of big data. The use of big data and knowledge management systems has proven to benefit stakeholders and customer-facing departments across organizations including, C-level executives, business operations, and risk management professionals. However, the real challenge lies in interpreting the huge troves of unstructured data gathered from disparate sources.

A major challenge for most businesses today revolves around their inability to gather and process massive data sets. Get in touch to learn how we can help you tackle this challenge.

Why is it a necessity?

Propelled by the paradigm shift towards digital transformation, businesses are now realizing the true potential of knowledge management and AI, and are categorizing it to be a key driver behind the digital transformation initiatives of every business.

A well-defined knowledge management process plays a pivotal role in enabling business transformation by building a sustainable and progressive business culture. Its benefits include the following:

Knowledge management and AI help improve productivity while paving the way for development and innovation in processes
Big data and knowledge management enable businesses to deal effectively with the changes in the market
Implementing a robust knowledge management process can help develop and align strategies with business objectives

As business leaders are leaving no stone unturned when it comes to digitizing end-to-end business operations, few are investing heavily to achieve the same results, i.e., increase revenue, reduce costs, improve customer satisfaction, and mitigate risks. The implementation of a knowledge management system can not just offer the right information to the right people at the right time but can help do so without negatively impacting the tail-spend and productivity.

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Establishing an Effective Vendor Evaluation Framework: Dos and Don’ts

Enterprises today choose to outsource a huge chunk of their core operations to third-party vendors. To make the most of these investments, businesses must evaluate vendors against a well-defined set of vendor evaluation criteria.

As the name suggests, vendor performance evaluation is a basic process of evaluating new and old vendors using a quantifiable approach. It holds a top spot in the agenda of every business irrespective of its sector since businesses have a huge portfolio of suppliers, and it’s essential to gauge their performance based on factors like contract compliance, cost reduction, and risk management. Moreover, as businesses expand their global footprint, vendors are handled by an increasingly large number of purchasing executives. In such a scenario, the lack of a vendor performance evaluation framework may intensify the challenge of fostering relationships with the right vendors, leading to huge losses.

In addition, the COVID-19 pandemic has shed light on the need to evaluate vendors’ ability to deliver the services and products you need to maintain critical operations under emergency conditions. Hence, while establishing a framework or while creating a vendor evaluation scorecard businesses must include factors that help gauge a vendor’s disaster and pandemic preparedness.

Building strong vendor-business partnerships depends on having a reliable vendor evaluation process in place to identify and gauge the potential of vendors. We can help you build such processes and track events in real-time, request a proposal to know more about our capabilities.

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To make vendor evaluation a cakewalk for our clients, we have developed easy to follow steps to create and establish a vendor evaluation framework. Adopting this vendor performance evaluation framework can help you compare the capabilities of different vendors to determine the best fit.

#1 Maintain a healthy vendor roster

Vendor categorization is the first step in developing an effective vendor evaluation system. Categorizing vendors into homogenous groups based on their offerings can help distinguish vendors based on the products and services offered.

#2 Analyze offerings based on the needs

The most crucial step in vendor performance evaluation is to understand what you can expect from a particular vendor. Once you’re fully aware of the capabilities of the vendors, you can identify the vendor that best meets your enterprise’s needs.

#3 Evaluate the vendor’s risk profile

The third most crucial step in vendor performance evaluation revolves around evaluating the vendor’s risk management ability. Since data security plays a pivotal role in all vendor relationships, it’s crucial to conduct periodic reviews, onsite visits, and audits on a regular basis. Doing so can help you evaluate the vendor’s performance against your company’s goals.

#4 Communicate with your in-house teams

To maximize success, its crucial to streamline processes. Since internal teams will be working with the vendors when the need arises, its crucial to communicate with your executives regularly regarding the importance of the relationship and how they can help support your efforts.

#5 Set vendor evaluation benchmarks

Businesses must establish vendor performance evaluation benchmarks while working with third-party vendors. Setting thresholds can also help you track and evaluate the performance of your vendors on an ongoing basis. Whether you decide to perform this evaluation on a monthly, quarterly, or annual basis, you need to perform your analysis based on previously established goals.

#6 Establish an active feedback loop

By establishing a feedback loop, businesses can continually monitor and take necessary steps to improve vendor performance regularly. To obtain the best results, companies must begin by generating performance requirements and then set up multiple options for feedback.

Boost effectiveness and profits by building powerful, automated vendor performance evaluation systems. Speak to an expert for detailed insights.

What are the don’ts in the vendor evaluation process?

Vaguely formulated requirements

Unclear requirements leave room for interpretation. As such, vendor responses will be based on assumptions, which will further aggravate your challenges in evaluating vendor responses.

Communication indiscretion

Whether a deliberate attempt to provoke conflict or not, giving out information about a competitor’s pricing strategy to another vendor can jeopardize the whole process and severely harm your credibility in the long-run.

Disregarding the proof of concept

A common mistake is to gauge a vendor’s capability solely on the proposal and not their ability to meet your business requirements. Hence, analyzing the proof of concept must hold a top spot in your vendor evaluation checklist.

Based on the criteria mentioned above, it is quite evident that setting standards for vendor evaluation can benefit both your organization and the vendors by helping build stronger business-vendor relationships. However, businesses must keep abreast of the current market trends and monitor the vendor landscape periodically to find new vendors that comply with guidelines and meet specific requirements.

Using a vendor selection scorecard or a vendor rating system for your vendor roster is crucial and helps discern vendors based on the abilities. Request a FREE demo to know how we help businesses in establishing a robust vendor evaluation process.

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Propensity Score Matching in Clinical Research: Advantages, Limitations, and Applications

Propensity score matching (PSM) is a widely used statistical method in clinical research, which leverages the power of natural language processing, statistics, and data science to generate meaningful insights by connecting thousands of data points. With clinical research becoming increasingly multifaceted, the corresponding data sets have also become more intricate, posing multiple challenges to the estimation and use of propensity scores. Though the growing use case for propensity analysis in this field can be attributed to several factors, the primary reason revolves around the availability of huge volumes of randomized, unstructured data.

Notably, its popularity also stems from the need to analyze data and compare treatment groups with the confounding baseline variables. Propensity score matching also aims to compare treatment groups with measured baseline variables to achieve an apples-to-apples comparison while reducing the bias due to confounding.

Leading businesses prefer Quantzig due to its ability to instantly discover niche areas where data and analytics can drive growth. Request a FREE proposal today.

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Advantages and Limitations of Propensity Score Matching

Enhance process transparency: Propensity score matching primarily aims to compare treatment groups with covariates, making it easier to communicate the results through graphical representations and interactive dashboards. Besides, propensity analysis offers insights into the quality of data, ensuring complete transparency of end to end processes.

Gauge the impact of treatments and drug formulations: Propensity score matching enables researchers to accurately gauge the impact of treatments or new therapies, which may otherwise be deemed invalid due to the imbalance between treatment groups.

A significant limiting factor is that propensity score matching only accounts for observed and observable covariates. Since it only controls observed variables, any hidden bias due to latent variables may go unnoticed post the analysis. Another quantifiable issue is that it requires large samples, resulting in the considerable overlap between various aspects of treatment and the control groups.

Applications

Among all the techniques that leverage propensity scores, propensity score matching is gaining prominence due to its ability to reduce the impact of selection bias when estimating the treatment effects in observational and randomized controlled trials. Few applications of this frequently used method are listed below –

Treatment analysis
Estimation of randomized controlled trials
Clinical outcome analysis

Creating a dynamic, scaleable propensity score model that is capable of demonstrating ROI is crucial to succeeding in the long run. Get in touch to learn how we can help you build one.

Undeniably propensity modeling solutions that leverage techniques like Propensity Score Matching (PSM), Propensity Score Stratification (PSS), and Propensity Score Weighting (PSW) are turning out to be useful in generating data-driven insights across industries. These insights are also opening up new opportunities that enable businesses to improve customer retention, enhance marketing campaigns, minimize risks, and reduce spend while driving decision-making.

As far as propensity score matching is considered, it can help analyze the underlying implications of factors that impact engagement rate, customer behavior, churn, and the willingness to pay for certain services. However, the successful implementation of propensity score models is deep-rooted and depends on the use of efficient data acquisition strategies, availability of high-quality data, and an impactful use case. This plays a crucial role since the lack of useful data makes it hard to find associations and patterns that drive consumer behavior and decision-making. Therefore, the successful application of propensity score matching can be fully realized when companies gradually transition to a data-driven culture with operations and decision-making based solely on innovative technologies and proprietary tools.

Quantzig’s approach to propensity analysis is unique in every aspect and can help you make the most of your investments, request a demo for detailed insights.

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Why End to End Supply Chain Visibility is Still a Major Concern for Retailers

In the new normal, retailers are poised to witness massive pressures to optimize operations and deliver seamless services via multiple channels. But the predominant omnichannel environment within retail has made collaboration, optimization, and the management of end to end supply chain visibility a major challenge for global retailers.

To tackle these challenges, retail companies involved in the production, movement, and sale of physical goods must begin by organizing their increasingly complex global supply chains to meet the increasing demand via online channels. While gaining real-time end to end supply chain visibility might not sound like an easy task, it is a necessary evil that plays an active role in helping retailers adapt to the evolving supply chain dynamics and mitigate disruptions.

Here are the top four challenges that are driven by the lack of end to end supply chain visibility in retail.

Our ability to evolve and improve our offerings helps organizations to address their most complex, pressing retail supply chain challenges right from logistics optimization to operations management. Request a proposal to learn more about supply chain visibility analytics.

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Analyzing the Growing Importance of Supply Chain Visibility in Retail

As retail supply chains grow more sophisticated, lead times are becoming a matter of grave concern. Moreover, the convergence of physical and digital platforms have made it practically possible to track and monitor events in real-time. The advancements in sensor technology have also made it possible for objects to communicate and collaborate directly with minimal to zero human intervention. With so much embedded intelligence and new opportunities driven by technology, supply chain visibility has now progressed from being a decision support tool to decision delegation and a core predictive capability. As retailers begin to adapt to the new normal, we are poised to witness the emergence of a unique, smarter supply chain with three core characteristics- streamlined, interconnected, and intelligent.

Factors influencing the need to improve end to end supply chain visibility in retail:

Expansion of retail operations and the need to comply with regulations

The need to allocate and proactively manage inventory held at various stages in the supply chain

Rising stakeholder demand for accuracy and timeliness of inbound and outbound shipment events

Growing concerns around supply chain operations management, speed, and accuracy

The business mandate to enhance cost efficiency by reducing supply chain execution costs

Having played an active role in supporting the supply chain decisions of the most innovative and successful retail businesses, we hold a proven track record of running world-class global supply chains. Speak to our retail supply chain visibility analytics experts to learn more about our engagements.

What sets us apart?

At Quantzig, we understand that providing multi-channel delivery while ensuring consistent customer experiences is crucial for retailers in the current business setting. To help our clients from the retail sector address this issue, we provide secure, sustainable, real-time end to end supply chain visibility solutions that empower them to expand their global footprint and reach every market that matters, both now and in the future.

Our end to end supply chain visibility solutions for retail covers various aspects of supply chain operations management, including:

Distribution center and freight analysis

Logistics and transportation analytics

Demand and sales forecasting

Quantzig’s end to end supply chain visibility solutions support inbound logistics, distribution, returns capabilities in ways that enhance inventory management, reduce total operating costs, and improve cycle times. Request a FREE demo for detailed insights on how supply chain visibility benefits an organization.

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Mastering Human Resource Management with Predictive HR Analytics | Quantzig

The ongoing seismic shifts in the HR landscape have prompted IT service providers to embrace a data-driven culture to acquire and retain top talent. Having realized a manhunt to acquire top talent would not suffice in today’s world, organizations are leveraging HR technologies that apply predictive HR analytics to gauge factors like employee performance, churn rate, and other similar metrics.

However, aligning corporate goals with your HR strategy plays an equally important role in effective human resource management. Based on a deep-dive analysis of the challenges facing HR teams, Quantzig has brought together technologies such as machine learning, artificial intelligence, predictive analytics, and natural language processing to help its clients act on insights and streamline workforce planning processes.

Looking for more advanced analytics solutions to stabilize business operations? We’ve got the right solutions, request a free proposal right away!

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How HR Teams Within the IT Sector Can Use Predictive HR Analytics to Drive Outcomes

The advancements in HR technologies have shed light on the benefits of predictive HR analytics, which is now emerging to be a useful tool for determining the direction of an organization’s growth. Once perceived as an isolated function, ‘human resource’ is now a meaningful contributor to an organization’s overall business outcome.

Let’s discuss critical areas where predictive HR analytics can help drive positive business outcomes.

Employee Data Management: Determine the type of data sets required, and the best methods to collect, integrate, and manage employee data with minimal effort

Data Modeling: To make HR analytics an integral part of your business decisions requires a robust and well-defined operating model

Data Dashboarding and Reporting: Select appropriate HR analytics technologies based on your specific reporting and dashboarding requirements

Owing to the rising complexities within the information technology sector, one gets to witness a proportional increase in the adoption of predictive HR analytics technologies. Apart from its contribution to the existing challenges, constant market changes are driving significant transformations that make building technical and analytical competencies crucial for HR teams.

We help businesses create intelligent workflows and safeguard mission-critical processes with ongoing support and real-time insights. Speak to an expert for comprehensive insights into our predictive HR analytics solutions.

Why Choose Quantzig?

Our experience in the field of analytics has helped us understand the uniqueness of businesses, especially when it comes to human resource management. As such, choosing a predictive HR analytics dashboard that is specific to your business requirement is critical to driving positive outcomes. Hence, we have developed a comprehensive suite of predictive HR analytics solutions with customizable dashboards and easy to use interfaces. By leveraging our predictive HR analytics solutions, HR executives within the IT sector are likely to spend less time and resources in making assumptions, and can instead rely on insights to take actions that drive operational excellence.

Our predictive HR analytics capabilities include:

Employee performance analytics

Employee acquisition analytics

Employee attrition modeling

Collaborating with us can help you stay prepared to execute your business strategy with the right people, skills, and technology.

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Demand and Supply Planning: 5 Action Points for Demand and Supply Planners to Succeed in the Post-COVID Era

The growing complexities of IT supply chains, coupled with the crisis-induced challenges, have transformed the IT industry into one in which traditional demand and supply planning practices can no longer help sustain vulnerabilities or respond to dynamic market conditions. Also, the exponential growth in multiple data sources within the IT industry has necessitated an end-to-end supply chain redesign across all verticals.

The rapid influx of data along with the need to adopt a more sophisticated demand and supply planning approach is further amplified with developments in the field of AI and analytics, empowering businesses to analyze the market and execute more intelligent workflows and strategies. According to our experts, these technological disruptions have played an instrumental role in the demand and supply planning transformation efforts of enterprises across the globe. As a result, leading businesses are now capitalizing on new opportunities to become more demand-driven in their approach to demand and supply planning.

This article, by Quantzig, sheds light on the need to focus on demand planning optimization, demand and supply planning challenges, its impact on IT supply chains, and critical business benefits.

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Supply Chain Management Begins with Demand and Supply Planning

Given the dynamism within the IT sector, businesses need a more comprehensive demand planning and forecasting framework. Also, since it plays an integral role in processes like supply chain management (SCM), the focus on demand and supply planning has now increased globally. By making use of industry-leading solutions to develop accurate demand and supply planning strategies, companies can gain insights into business-critical functions like customer relationship management and supplier relationship management, both of which are critical links within the supply chain.

Benefits of Deploying a Strategic Approach to Demand and Supply Planning

Reduce stock-outs by improving in-stock availability
Analyze demand swings and build effective strategies to manage growth
Build cohesive supplier relationships and gain greater visibility into processes.
Better assortment and allocation across all channels
Improve productivity of planners across all tiers of supply chain

Five action points to thrive in the ‘new normal’

1. Identify factors driving future demand planning and optimization

2. Analyze the dynamism in IT supply chains

3. Restructure demand and supply planning processes

4. Prepare data for the recovery phase

5. Redesign product portfolios

Get in touch with our demand and supply forecasting experts to gain detailed insights into factors impacting your supply chain network.

Why Choose Quantzig?

Quantzig is a leading analytics solutions provider specializing in several analytics domains, including digital analytics, pricing analytics, manufacturing analytics, and supply chain analytics. We collaborate with clients from different sectors to help them identify opportunities, tackle disruptions, and transform end-to-end business processes. Through our advanced analytics solutions, we combine deep analytical insights with the dynamics of the markets and work closely with clients enabling them to make the most of their analytical investments by driving positive outcomes, building sustainable processes, and securing lasting results.

What makes our offerings unique, you ask? Unlike the others, our approach to developing accurate demand plans enable businesses to reprioritize supply chain processes based on changes within the internal and external business environment. Our supply and demand planning optimization solutions also align demand with market fluctuations and a host of other factors that play a crucial role in neutralizing the impact of out-of-stocks.

Request a demo of Quantzig’s demand planning and optimization solutions to learn how we help businesses forecast and optimize demand using the best demand forecasting methodologies.

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Strategic Sourcing and Procurement: Empowering sustainability in a circular economy

Propelled by market dynamism and the inclination toward modernization, original equipment manufacturers (OEMs) operating in the IT industry continue to harness the power of globalization to drive productivity. In such a scenario, strategic sourcing and procurement have taken center-stage, becoming inevitable in driving better business outcomes. Notably, strategic sourcing and procurement have transformed into a more strategic business function that is closely aligned to key objectives and business goals. Also, as disruptions due to economic and political volatility have rendered the IT industry fiercely competitive, businesses are now looking to sharpen their strategic sourcing and procurement skills to maximize performance and drive efficiency to gain a competitive edge over their peers.

Strategic sourcing and procurement can help shorten the development timeframe and meet cost targets to make the design and development of quality products in the competitive IT industry a repeatable reality.

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How OEMs Can Tackle Supply Chain Disruptions Using Quantzig’s Strategic Sourcing Solutions

Given the rise in supply chain disruptions, a suitable approach that OEMs can adopt to drive efficiency is by closely examining sourcing and procurement processes to optimize and streamline core operations, both of which play a pivotal role in improving supply chain visibility. At Quantzig, we help you adopt a transformational approach to achieving high performance through strategic sourcing by offering advanced supplier scorecarding and visibility solutions. When compared to our peers, we go a step further and crawl the web for latest updates on the current trends and provide insights to our clients on factors that will affect the supply side of the business, thus enabling the sourcing and procurement function to play a crucial role in proactively engaging new suppliers and procuring alternate raw materials.

Quantzig’s strategic sourcing and procurement services focus on identifying and evaluating solutions-oriented suppliers that provide goods and services that benefit OEMs operating within various industries. The aim is to analyze factors impacting indirect, direct, and raw material spending through cross-collaboration and strategic purchasing execution. This includes, but is not limited to areas of spending that involve-

Equipment maintenance and operations management
Packaging and distribution
Corporate materials and services

Get in touch with our strategic sourcing and procurement analytics experts to learn how we can help you mitigate manufacturing and procurement risks with minimal effort and investment.

Case in Point: How Quantzig Helped a US-based Tech Giant to Reimagine its Sourcing and Procurement Strategy

With operations spread across 15 countries and over 1,000 suppliers, procurement has always been the lifeblood of this US-based Tech major. However, long-entrenched strategic sourcing processes and siloed data sets across this heavily matrixed enterprise were giving rise to major challenges that curtailed their sourcing and procurement efficiency. Realizing the need to revamp its current supply chain processes, the client approached Quantzig looking to leverage its strategic sourcing and procurement services to enhance efficiency.

A detailed analysis of the client’s challenges helped reveal that the client needed to break down silos to gain visibility across the organization. To do so, Quantzig set up a cross-disciplinary team of supply chain analytics experts, procurement specialists, and process consults, who developed advanced data cleansing and enrichment techniques and offered rich data-driven insights within weeks. This was followed by the creation of a strategic sourcing and procurement analytics platform with a comprehensive suite of applications designed to address the full source-to-pay continuum.

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