Digital Transformation in Recruitment

A few years ago, the impact of digitization was only established in top industries like Banking, Insurance, and Retail. Now times have changed – the recruitment industry is also adopting digital transformation.

Everyone is a candidate at some point in their journey. Whether you are an employer or a candidate searching for a job, the digital transformation is helping the recruitment industry to implement smarter hiring strategies.

Recruiters are the brand ambassadors of a company as they are the first people with whom a candidate interacts. But getting the right people with the right skills, at the right price, has been a long-running headache for recruitment teams.

It’s a competitive marketplace for talent, with demand for skilled labor far exceeding the supply of qualified candidates actively looking.  This makes it more important need for recruiters, to master new digital techniques to find, reach and engage right skilled potential candidates.

Candidates seeking jobs in the market are also now tech-savvy and expect fast and easy application processes and communication. Their behaviors and preferences are changing. Power has transferred from recruiter to candidate.

There are multiple ways digital can help:

Assess the digital footprint of the candidate: Recruiters can use this data to get important insights into the skills of potential candidates. Correlations between social media profiles can reveal important aspects such as interests and hobbies, as well as an overview of the candidate’s personality. How suitable is the candidate to an organization’s culture can be assessed based on her/his social media sharing habits on subjects like gender, age, race, and politics.

Online language/skill assessment:  It is one of the easiest ways for companies to filter through the pool of candidates efficiently. Recruiters can ensure the quality of their hires via psychometric and other tests.

Online job portals:  Monster, Glassdoor, Indeed, Naukri and TimesJobs have helped in reaching out to candidates across different geographies and industries. They have also helped in building good candidate pipelines for recruiters. LinkedIn has started this revolution long back and has the credibility of companies as well as candidates equally.

Advantages of Digital Transformation in Recruitment:

·      Your website messaging can be targeted to different candidate personas

·      Candidates can easily engage with your company on social and mobile

·      Helps create the company brand in the digital world

·      Machine learning is helping is processing piles of applicants to find the right candidate

·      The organization can nurture candidates over time by relevant job alerts, talent campaigns

·      Social media presence generate the better response from talents to the brand

·      Digitization helps in ease of entire recruitment process and in turn happy candidates

·      Job seekers get an inside view of a company through a site like Glassdoor, which includes information on compensation, organizational culture, career progression, learning opportunities, etc.

·      Through the use of Big Data, learning companies can find suitable candidates, cut recruitment time and costs

·      Consolidated database of CVs becomes a powerful mining tool and cost saver

Digital is helping to convert the chaos of recruiting into “Smart Recruiting”.

Digital disruption in Telecom sector

Digital disruption has turned the telecom industry upside down. New digital technologies are entering the market forcing telecom operators to adapt to new business models.

We went from analog to digital few decades back and then GPRS, Edge & came 3G, which brought data and web services to us. With 4G and smartphones now customers have the power of the supercomputer at their fingertips.

After iPhone, smartphones are penetrating deeper in many countries. Carriers now have to focus on customer churn more than on acquiring new ones. Today telecom operators are leveraging big data technologies to analyze call pattern data to better understand their customers’ habits and predict their requirements and thus offer better services at right time and price.

Operators are using analytics to identify customers at risk of default in bill payments and optimize their outreach for higher collection.

Today with so many disrupters, telecom companies have to think of survival. SMS or text message & MMS were some of the core services just a few years back, and then came WhatsApp, which changed all the communication paradigms. Further Skype, Viber, WeChat have entered the market to pressure the prices down for text and voice.

With the digital age, telecom companies have to:

·         Add new services to capture consumer’s attention

·         Accelerate time to market these new services with technology advancements

·         Map end-to-end customer journeys  from acquisition, engagement, retention

·         Use Big Data Analytics to focused market segmentation and hyper-personalization

·         Automate customer care and digital self-service options

·         Revamp website and give customers access to personalized information, offers and buying options

Leaders like Vodafone, Verizon, AT&T have leveraged all the digital technologies to reach out to their customers in a most efficient way.

Digital payments via mobile wallets have become a boon for telecom, as mobile payments are generating tons of Big Data on shopping behavior & preferences, enabling more sales opportunities via targeted marketing

Many technology players such as Apple, Samsung, and Google are collaborating with telecom players to make consumer’s life easy.

A good customer experience is now essential with help of digital. We live in a time when convenience, personalization, and speed are the bare minimum people expect and telecom companies have to take aggressive measures to exceed these expectations.

Digital Transformation of Healthcare

The digital transformation storm is sweeping various businesses like retail, banking, insurance, media, and travel and has entered into our personal lives.

Another industry that has joined the above list by being hit by the storm is the healthcare.  

The advancements in digital technologies like cloud computing, mobile communications, advanced analytics and the internet of things have positively helped healthcare.

Healthcare companies are among the most heavily regulated, facing unique compliance challenges. They were always struggling to figure out how to integrate, aggregate, harmonize and analyze all of the data they have captured, to discover actionable business insights.  Further, accelerated time to market and adding value to patient’s lives are the key drivers for digital adoption.

Digitization of healthcare has gone beyond the drug development. It is no longer providing the drugs alone but services as well.

The healthcare industry had witnessed an impact on the entire product life cycle starting from the early drug development to delivery and finally patient care. Drug discovery is immensely helped by machine learning. Researchers will have access to much more detailed analysis on real-world data, which will assist in better understanding the effects of a drug.

Internet of Things is used to digitally transform manufacturing and supply chain. Temperature sensing tags are used to monitor cold chain conditions and thus ensure and maintain product quality in transit.

Electronic Health Records of any patient who is under the care of multiple doctors helps them to use these valuable data points to deliver appropriate treatment and make decisions about patient’s care.

Wearables have improved the patient care substantially. There are many wearable devices that provide real-time monitoring of disease symptoms along with reminders for prescribed treatment. Ingestible medicines like Proteus pill sends patient data in a secure transmission to the physician, which helps in more accurate diagnostics and personalized treatment.

Fitness wearables such as Fitbit and Apple Watch have increased the ability of patients to take responsibility for their own health.

Portals like “PatientsLikeMe” are helping people with chronic health conditions get together and share their experiences living with the disease. Where newly diagnosed patients can improve their outcomes by connecting with and learning from others. Also, researchers learn more about what is working and what is not, so that they can develop new and better treatments.

Patient engagement has become easy with mobile apps for recovering patients to help manage stress, find information, learn about caregiving and chat with a doctor.

In clinical trials, digital is helping by standardizing data exchange and replacing several data repositories with a centralized information hub. Patient finder technology combines clinical knowledge with big data to allow drug manufacturers to identify potential patients that may have a disease that is hard to diagnose.

With Telemedicine, Patients no longer have to schedule their routine follow-up visits but they can a video call to get the prescription update or check-up they need.

With digital, consumers are now in the driving seat. They have better access to quality doctors and quicker wellness. Digital is helping healthcare and humanity.

Mobile Analytics and impact on Digital Transformation

Mobile usage has surpassed the desktop usage a few years back and is fast becoming consumer’s preferred portal to the internet.

Always-on consumers spend more than 70% of their media consumption and screen time on mobile devices, and most of that time in smartphone apps.

Analyzing their behaviors, understanding their needs, complaints and proactively using that for revenue growth, is essential in today’s Digital Age.

Mobile analytics captures data from the mobile apps, websites, and web app visitors to help companies improve retention, engagement, and conversion.

Mobile analytics is similar to traditional web analytics (used for desktop browsers and applications) in that they identify unique visitors and record their behaviors.

Mobile analytics is generally split between mobile web and mobile apps. Mobile web refers to when individuals use their smartphones or tablets to view online content via a mobile browser. While mobile apps analytics works on the apps downloaded, installed and used for further insights.

Mobile analytics gives companies unparalleled insights into the otherwise hidden lives of users. It gives insights about what users engage with, who those users are, what brings them to the site or app, and why they leave.

How different departments are using Mobile analytics: 

• Marketing: Tracking campaign ROI, segmenting users, automating marketing
• UX/UI: Tracking consumer behaviors, measuring user experience

A typical mobile analytics platform should be able to:

• Offer a unified view of the customer: Track data across operating systems, devices, and platforms 
• Measure user engagement: For both standard and custom-defined events
• Segment users: Create groups based on location, device, demographics, behaviors, and more
• Offer dashboards: View data and surface insights with customizable reporting
•  A/B test: Test features and messaging for performance
• Send notifications: Alert administrators and engage users with behavior-based messaging

 There are three major types of mobile analytics:

• Advertising/Marketing Analytics – covers how many installs, opens, clicks, purchases, registrations, shares etc.
• In-App Analytics – covers type of device, location, event tracking, language etc
• Performance Analytics – covers app uptime, crashes, errors, responsiveness etc.

Marketing analytics enables you to allocate your ad spend to right customers.

In-app analytics helps you to understand your users are and their interactions with the app.

Performance analytics helps in keeping your apps stable and your customers happy.

Google Analytics is one of the free tool available and then there are multiple commercial products available for organizations to use.

Mobile Analytics can help you realize the entire user experience of your mobile app – from detection to download to engagement.  

Through actionable insights at each stage of the app lifecycle, marketers and developers can create an app experience that is more useful and be engaging for their users and improve overall marketing strategy.

The role of Analytics in Digital Transformation

Today every industry is talking about Digital Transformation and affected by technologies like the Internet of Things, Blockchain, Microservices and Cloud. Every company like Apple, Nike, and Nestle, better known for their brand products have now become Technology Company.

However, for every technology the powerhouse behind the success is Analytics.

Look at the latest trend of Internet of Things – Sensor technology can emit data every second or millisecond and with help of Cloud, storing this humongous data is like a piece of cake. 

Only storing this data is not going to add any value to the business, unless it is analyzed for actionable real-time insights. This is possible with a variety of analytics algorithms, which provide business value like predictive maintenance, optimized supply chain; smart equipment’s who order on your behalf and the list goes on.

Customer experience has become the most important driving factor of Digital Transformation. Companies like Amazon, Apple or Disney have embraced the power of analytics to understand their customers and provide unmatched customer experience.

As we move into 2018, digital is seen as core competency than innovation. Consumers are no longer satisfied when they are treated as a group of people but they expect hyper-personalized touchpoints. Advanced analytics embedded in each interaction, transaction, and process is driving the next wave of productivity and growth.

Businesses are using advanced analytics like Artificial Intelligence, Deep Learning, and NLP for various insights.

The mobile first strategy has given business the ability to reach their customer anytime, anywhere, on any device. We cannot go for 1 hour without using an app on our smartphone. Tons of data is generated with this easy to use technology, whether we are using it to find a nearby restaurant, paying bills or navigating through the unknown city. Mobile analytics can help organizations understand their customer behaviour and increase monetization of apps and overall revenue.

Real-Time analytics helps to get the right products in front of the people looking for them or offering the right promotions to the people most likely to buy. For gaming companies, it helps in understanding which types of individuals are playing which game and crafting an individualized approach to reach them.

Digital Marketing is hugely benefited by Analytics due customer analytics, brand analytics, competition analytics and conversion analytics.

Today, why Analytics is playing important role in digital, is due to the amount and variety of data generated is skyrocketed.  Making forward-looking proactive decisions is possible via forecasting, optimization, predictive analytics and text mining.

Data is the new oil, but it is crude, and cannot really be used unless it is refined with analytics to bring the new gold nuggets.

Top 5 Big Data use cases in Digital Age

Today data volumes are growing exponentially and it is coming from various sources like sensor data from the Internet of Things, log files, social media files like audio/video, call center call logs and all the organization internal data. 

An organization who harness this data and exploit it for their advantage are surviving the competition even from nontraditional players.

Big data has become the foundation for digital transformation.

Though the big data opportunity is growing rapidly, the top two big data challenges that organizations face are determining how to get value out of big data and defining a big data strategy.

Unless you acquire, store and retain the internal data from organization coupled with all the external data from call logs, audio/video files, customer surveys etc. there will be fewer chances of applying analytics on top of it.

Here are top 5 use cases businesses are deploying to get a competitive advantage.

1.   Customer 360-degree view: A lot of companies had problems integrating large bulk of customer data between various databases and warehouse systems. They are not completely sure of which key metrics to use for profiling customers. Hence creating customer 360-degree view became the foundation for customer analytics. It can capture all customer interactions which can be used for further analytics.

2.   Fraud detection and prevention: Financial crimes, fraudulent claims and data breaches are the most common challenges faced by organizations across various industries. Thanks to big data analytics and machine learning, today’s fraud prevention systems are much better at detecting criminal activity and preventing false positives. Today with help of Big Data platforms, banks can store all the historical data they have which can help in better fraud detection.

3.   Recommendation engines: In this digital age, every business is trying hyper-personalization using recommendation engines to give you a right offer at right time. organizations that haven't taken advantage of their big data in this way may lose customers to competitors or may lose out on upsell or cross-sell opportunities

4.   Sentiment Analysis: Today, it is important to know consumer emotions while they are interacting with your business and use that for improving customer satisfaction. Big data and social media channels together help in analyzing customer sentiments which gives organizations a clear picture of what they need to do to outperform their competitors. Disney, Nestle, Toyota is spending huge money and efforts on keeping their customer’s happy.

5.   Predictive and preventive maintenance: With internet of things and sensor technology data is captured from machines, equipment, and devices in real time. All the data is put to use for predicting the failures up front and reduce unplanned downtime and maintenance costs. Companies like GE are using Digital Twins in their wind farm to drive down the cost of electricity.

Big Data is nothing new today and companies are building data lakes to take advantage of storing and retaining any number of years’ worth of history.  

There are many more use cases but which other use cases you can think of that measure the success of an organization?

3 building blocks of Digital Transformation

Today almost every industry is experiencing significant digital disruption. Every business is eager to get on this bandwagon and strive to survive. CEOs are facing this biggest questions of how to transform the organization?

Digital Transformation has come as big tsunami wave, either you can ride it like an expert surfer, or go under and get to the bottom.

Companies start the process of transformation but more often fail to integrate across departments and take advantage of intelligence it generates.

There are 3 building blocks to start with baby steps and they are:

Integration, Intelligence & Impact.

How do you use these 3 building blocks to achieve digital transformation?

Integration: Integrate Organizational data & employees, as digital technologies bring greater connectivity between people and processes.

·        Acquire an ability to acquire, store, retain & track data about every process and customers. Use the big data as a foundational platform. This ability offers a unique opportunity for a company to become a truly responsive organization offering rapid quality improvement and learning.

·        Create a transparent repository or sharing mechanism of the efforts undertaken across the company’s different departments. This helps market the successes and boost the morale of the teams.

Intelligence: Intelligence, with digital technologies brought by exceptional amounts of data of business ecosystems from consumers to competitors.

·        Social Listening: In today’s world it is extremely important to gauge the brand perception by the consumer. This typically involves acquiring basic social media analytics skills giving instant access to online conversations and activities about brands and topics. These reveals opportunities to increase brand awareness and reputation.

·        Digital Insights: By applying visualization on data from external social conversations to internal organization which help to optimize operational decision-making

·        Digital Foresight: By utilizing analytics on top of all the data and integrate these insights at a strategic level. These foresights from consumers, competitors provide an ability to take a corrective course of action on the future decisions.

Impact: The Impact relates to the kind of customer value a company can bring by leveraging digital which builds the brand loyalty.

·        Digital Technologies like Mobility, APIs, Microservices create a tremendous opportunity to connect with customers.

·        Driving Engagement: Systematically using digital and non-digital interactions and involvement from customers to increase value.

·        Leading Disruptions: Use digital technologies to produce a self-generated stream of innovations whereby products and services are continuously improved.

Use these building blocks for taking baby steps in digital transformation. Later apply the strategy, culture, and operation plan to execute without fail.

Digital Transformation in the Fashion Industry

Gone are the days when brand communication was mostly made up of ads that appeared on billboards, in magazines and/or on television. Today, all of this is augmented with Digital revolution.

The fashion industry is engaging with digital technology in new and different ways, in order to stay competitive and to engage with the ways that consumers are searching for jewelry, clothes, and accessories.

Technology is turning the fashion industry inside out. Today, consumers are most active as digital shoppers in the Fashion industry and are demanding a heartening digital experience across channels. People love the brick-and-mortar stores but also exploit online channels through social media, while on the go and online. These Omni-channel experiences should provide customers with a “wow” factor and Digital Transformation is the way to achieve this objective.

In today’s fashion world, competition is fiercer than ever, giving consumers’ far greater power & they demand only the very best customer service. Most of the fashion brands now have a social media presence on Pinterest, Instagram presence, tapping into our heightened engagement with imagery.

It can take many years to build a successful brand, but only a short time to destroy it. Fashion brands have always needed to be ready and able to respond to issues of uncertainty, risk, and reputation, all at varying times.

Burberry is the posterchild in digital for fashion that started with live streaming runshows. Then came iPads and mobile apps for consumers to try out different outfits.

In Paris, a window front invites passers-by to download the Louis Vuitton Pass app in order to interact with the window and explore.

L’Oréal has put up a 'social wall' on its main website so consumers can share posts while shopping.

Harrods is the latest luxury retailer to transform its in-store experience with digital technology. They have many new super-high resolution stairwell displays at the flagship Knightsbridge, London store

Adidas has a store wall which shows shoe collections in 3D to see shoe designs from all angles.

With this availability of streaming big data and resultant analytics, fashion brands use the insights for hyper-personalization, align consumer experience and to track customer trends. The customer’s data is the core component of digital transformation in the fashion industry. So, hyper-personalization of mobile retail experiences will be huge in the near future.

Today, dressing rooms enhanced with augmented reality and social media features have transformed the shopping experience altogether. L’Oreal, Maybelline have already started testing special kiosks that enable shoppers to virtually try on makeup by simply taking a picture.

Even the most successful digital retail experiences are built from desktop experiences but the future is in mobile with a predicted 80% of sales traffic coming via this medium.

With digital at a side, fashion weeks across London, Paris, Milan & New York witness runway shows streamed online, Instagram & snapchat stories in real time, creating a close connection between consumers and brands. 

Are you drowning in Data Lake?

Today more than ever, every business is focusing on collecting the data and applying analytics to be competitive. Big Data Analytics has passed the hype stage and has become the essential part of business plans.

Data Lake is the latest buzzword for dumping every element of data you can find internally or externally. If you Google the term data lake, you will get more than 14 million results. With an entry of Hadoop, everyone wants to dump their silos of data warehouses, data marts and create data lake.

The idea behind a data lake is to have one central platform to store and analyze every kind of data relevant to the enterprise. With the digital transformation, the data generated every day has multiplied by several times and business are collecting this consumer data, Internet of Things data and other data for further analysis. 

As the storage has become cheaper, more data is being stored in its raw format in the hopes of finding nuggets of information but eventually, it becomes difficult. It is like using your smartphone to click photographs left, right and center, but when you want to show some specific photograph to someone it’s very difficult.

Data Lakes, if not maintained properly, have the potential to grow aimlessly consuming all the budget. Some companies have their data lakes overflowing on-premise systems into the cloud.

Most data lakes lack governance, lack the tools and skills to handle large volumes of disparate data, and many lack a compelling business case. But, this water (the data) from your data lake has to be crystal clear and drinkable, else it will become a swamp.

Before getting on the bandwagon of creating the data lake that may cost thousands of dollars and months to implement, you should start asking these questions.

·        What data we want to store in Data Lake?

·        How much data to be stored?ilo

·        How will we access this massive amounts of data and get value from it easily?

Here are some guidelines to avoid drowning into data lakes.

·        First and foremost - create one or more business use cases that lay out exactly what will be done with the data that gets collected. With that exercise, you will avoid dumping data, which is meaningless.

·        Determine the Returns you want to get out of Data Lake. Developing a data lake is not a casual thing. You need good business benefits coming out of it.

·        Make sure your overall big data and analytics initiatives are designed to exploit the data lake fully & help achieve business goals

·        Instead of getting into vendor traps and their buzzwords, focus on your needs and determine the best way to get there.

·        Deliver the data to wide audience to check and revert with feedback while creating value

There are many cloud vendors to help you out building data lakes – Microsoft Azure, Amazon S3 etc.

By making data available to Data Scientists & anyone who needs it, for as long as they need it, data lakes are a powerful lever for innovation and disruption across industries.