Lakshya - A Beacon of Knowledge, October 2019 Edition

EDITOR’S LETTER

“"With Evolution, Changes happen in every part of the world every day, every time."”

Welcome to the fifteenth edition of “LAKSHYA”, our monthly supplement designed for people who dare to think above the average and believe in connecting the dots. In an age where technology has taken over every sphere, information is abundant and data is omnipresent, we have planned to bring to you a collection of thoughtfully created and carefully crafted pieces of work by some bright aspiring minds of ICFAI Business School, Hyderabad on the current trends and receiving close review in the field of Operations Management and their relevance in different industries.

From the ninth edition, we created a new segment, ‘The Corporate Angle’ where article will be featured from prominent business leaders which will enlighten minds of young managers and business enthusiasts. IBS Hyderabad and Club Kaizen express a sign of gratitude to all corporate leaders for taking out time and scripting their thoughts for our magazine.

We look forward to providing you with some valuable insights and inculcate the passion for reading. We hope that you enjoy this issue and do let us know if there are any topics you’d look forward to be covered in upcoming editions.

Please write to us and become a part of this discussion Email ID: kaizenclub.ibs@gmail.com An Initiative by:

MAHESH HIREMATH JOINT SECRETARY – KORE Kaizen – IBS Hyderabad Batch 2018-20 1|K A I Z E N ’ S O P E R A T I O N S & R E S E A R C H E N T I T Y

CONTENTS

From the Mentor’s Desk

03

Are they really loyal? A shift from Satisfaction to Bonding

04

Retail Operations Turn around in Indian Economy

06

How does IKEA do it?

10

Formula One: The Race Behind the Race

12

Tourism Industry- A reality check

14

Role Of Data Analytics In Improving Operations

16

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From the Mentor’s Desk

In the era of competition, it is imperative for students to be prepared for the ever-changing business environment. Knowledge creation plays an important role to learn to tackle the dynamic nature of business.

I appreciate and congratulate the initiative of club KAIZEN for bridging the gap between corporate world and academia through LAKSHYA which is an excellent platform where industry practitioners, academicians and researchers can share their knowledge and experience, acting as a beacon guiding students to reach their goal.

My best wishes to club KAIZEN in their endeavour of knowledge creation through LAKSHYA.

Nishit Kumar Srivastava Mentor, Club Kaizen

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The Corporate Angle Are They Really loyal? A Shift from Satisfaction to Bonding Mr. Hrushikesh Kulkarni Insights Partner , LitmusWorld

Traditionally, Customer Satisfaction & Customer Retention has been viewed & spoken about by decision makers in the same breath. In reality, these two terms are like the two sides of a coin & necessitate a completely different approach in understanding, measuring these metrics to devise different strategies for actions. Both these Key Performance Indicators (KPIs) are essential not only for businesses to stay afloat, but also to add to shareholder’s value. Satisfaction is more about stated experience data towards a product/ service, on the other hand Retention is the demonstrated actual behaviour by your customers.

The basic difference is that while Satisfaction is stated in nature, Retention is about long term repurchase or relationship with the brand. For decades, clients, research agencies & management consultants have been tracking Satisfaction & have tried to draw a co-relation to the actual customer behaviour, but alas with only little success.

Satisfaction, Recommendation, NPS etc. the usually heard metrics in corporate board rooms (these are captured typically on a rating scale at an overall level for the brand & experience on a battery of different attributes more to pin point what next), does not take into account the volume or direction of the positive/ negative opinions, typically called the word of mouth, into the calculation. This is important, especially in today’s technology connected world, more to the likes of social media avenues like Facebook, Twitter, LinkedIn, Trip Advisor, Instagram etc. to name a few. It is critical to understand that a complete paradigm shift is needed to move away from the traditional approach and metrics, to look at more evolved & actionable metrics like Advocacy/ Bonding that the customer displays with the brand. In light of same, a few marketers have understood the benefits of having a dedicated social media team, who is responsible not only for service interventions, post a customer’s complaint, but also to arrest the negative spread on social media, so as to avoid any further tarnish to the brand, which if left uncontrolled can quickly erode the brand equity, that has been built over decades. The new metric will surely be one that needs some thinking with customer’s share of smart phones & tablets increasing with each passing day- digitalization.

Hence the bigger challenge is to understand what is Advocacy, its drivers & hence how to make the most of it for your brand. The closest definition being that it’s the brand commitment coupled with a strong positive, recurring yet voluntary casual communication on behalf of the brand.

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Some of the experiences with brands around us can be termed as pleasure or satisfaction in the subconscious mind, while some are painful, some are superficial, while some go deep inside us humans. They can create feelings and opinions, that can be a challenge to be articulated, but which causes customers to take action. The main objective of businesses hence should be to capture this ‘Moment Of Truth’ (MOT) as & when it happens & look at improving the brand’s experience, by reducing the pain points in the journey. The key is to understand the critical nature of touch points/ processes, their performance, brand perception and the inter-relationships within these levers. This is required throughout the customers’ journey, right from the information gathering stage, decision making stage (of-course with the influencer having played his/ her role), during the on-boarding process, right till the final consumption of product/ services, & stretches way beyond the purchase stage. The day companies start delivering on these aspects, we can safely say that customer expectations have been met, if not exceeded by the brand’s performance. The criticality lies in exactly understanding what customers really wants, whether they will stay or leave a brand and whether they will be loyal brand advocates acting even as Evangelists. This will in tune lead to a positive word of mouth, higher retention rate & a higher share of wallet and be a huge success story, to differentiate effectively over the competing brands.

The author, Hrushikesh Kulkarni, works as part of the Insights team with LitmusWorld, with more than 15 year’s experience in Marketing domain. He is an author to various research articles & teaches Research Methodology, Brand Strategic Management, Digital Marketing as visiting faculty at leading MBA colleges. A MBA in Marketing & BSc Mathematics is an avid traveller & also writes a travel blog called Distance Star.

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Retail Operations Turn around in Indian Economy

Dikshant Lodha (MBA 2018-20)

“It is well known fact that effective operations boost retail industry”

Indian retail industry is one of the most rapidly paced and dynamic industries in the world.

The total consumption expenditure is expected to reach nearly US$ 3,600 billion by 2020.

The retail sector contributes for over 10 per cent of the country’s Gross Domestic Product (GDP).

India is expected to become the world’s fastest growing e-commerce market, because of the robust investment in the sector and rapid increase in the number of internet users. There are various factors as second largest population in the world, urbanisation, connected rural consumers, rising household incomes and increasing consumer spending.

Increasing participation from foreign and private players has also given a boost to Indian retail industry. Global retailers such as Walmart, DMART, and JC Penney are increasing their sourcing from India and are moving from third-party buying offices to establishing their own wholly-managed sourcing and buying offices. India’s price competitiveness attracts large retailers to use it as a base of sourcing.

India is 77th in the World Bank’s Ease of Doing Business Ranking for 2019.

Under FDI schemes, there are some policies as – The Indian Government has introduced reforms to attract Foreign Direct Investment (FDI) in retail industry. India permits foreign direct investment in the multi-brand retail sector with a cap of 51 per cent ownership by overseas players and 100 per cent in single brand retail under the automatic route which is expected to give a boost to Make in India, and plans to allow 100 per cent FDI in e-commerce. India will become a favourable market for many retailers because there is the back of a large young adult consumer base, increasing disposable incomes and relaxed FDI norms.

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Problems & Challenges faced by Retail Industry Company takes some decisions without analyzing the market properly. So, it requires careful maintenance of day to day operations to remain at peak performance.

High overhead cost is also one of the biggest challenges. It can have a detrimental effect to a new or struggling wholesale business. Some common overhead costs such as – rent, labor, repairing, advertising, maintenance etc.

Overexpansion is also an issue as Supply problems, logistic challenges, staffing issues, and financing concerns are potential obstacles in expanding.

The sales will differ if changes in customer preferences and the market in general are ignored.

The economy periodically goes through low times. All the retailers who are unprepared for those times of economic recession are often caught off-guard financially.

Customer can be unhappy with your products. Preventive planning is the key. Maintaining clear lines of communication, reviewing customer profiles, and being quick to address customer concerns are all excellent ways to keep a minor problem from turning into a major disaster.

Subiksha Failure: Subiksha started its business in 1997 as a private limited company. After that it became public in 2005. It was doing good as it had 50 stores by 2000. The stores expanded rapidly in various formats with mobiles, electronics, groceries, medicines, consumer durables and IT without sufficient fund in hand.

But ultimately it failed by 2007-2008 because of      

It operated on very slim or zero margins as a result higher cash outflow.

Customer service was not well.

Poor supply chain management.

No fund for managing its operations.

Poor inventory management.

Under trained store managers The stores were not strategically places.

So, what are the operational solutions which can help a company to expand effectively?

1) Inventory Management- The efficiency of a retail store is based on the retailer’s ability to provide the right goods to the consumer, in the right quality, in the right quantity, at the 7|K A I Z E N ’ S O P E R A T I O N S & R E S E A R C H E N T I T Y

right place and in right time. The entire process of retailing depends on the efficient inventory management. Inventory includes: raw materials, semi-finished goods, finished products and supplies. An inventory system is the set of policies and controls that monitors the levels of inventory and determines that what levels should be maintained, when stock should be replenished, and how large orders should be.

2) Store layout Design & Planning- A retail store layout (whether physical or digital) is the strategic use of space to influence the customer experience. How a customer is interacting with your merchandise affects their purchase behaviour.

3) Omni channel in retail operations- Omni-channel refers to retailers with both a physical and digital presence. It is a modern approach to commerce that focuses on designing a cohesive user experience for customers at every touch-point. This is different from traditional marketing, where individual channels were optimized without necessarily taking the whole experience into mind.

4) Product flanking- Product flanking is a competitive marketing strategy in which a company produces its brands in a variety of sizes and styles to gain shelf space and inhibit competitors.

Companies who adopted these concepts: DMART DMart stores are owned by Avenue supermarts limited which is an Indian based company.

Total income of Rs.19,968 crores (US$ 2.86 billion) in FY19. It’s a chain of supermarket that offers customers a range of home and personal products like home utility products, food, toiletries, garments, beauty products, kitchenware, home appliances and others. It has a complete store layout system. The company offers its products under various categories, such as bed and bath, toys and games, dairy and frozen, fruits and vegetables, crockery, kid’s apparel, ladies’ garments, apparel for men, home and personal care, daily essentials, grocery and staples, and DMart brands. It has 176 stores in India at 163 locations such as Mumbai, Ahmedabad, Baroda, Bengaluru, Hyderabad, Pune, Surat etc.

WALMART Walmart is a renowned ecommerce business with an incredible model implemented to compete with other giants.

Walmart has 11,700 stores and serves about 270 million customers. Its business strategy is mainly based on “being competitive in terms of assortment, differentiating with the way

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people access, leading in terms of price, and delivering an incredible experience with the motto of EDLP (Every Day Low Prices).�

According to Walmart, Every Day Low Price (EDLP) is one of its ultimate commitments to control the expenses. It features an Omni channel presence in order to provide access to a wide collection of goods to its customers anywhere in the world.

Besides its massive physical infrastructure, seeing the growth of ecommerce, Walmart has been putting down huge investments in its digital platforms.

Road Ahead: Nowadays, Omni Channel of buying is turning into a desire wherein clients browse through the selection within the comfort of their homes, make a buying decision and simply need to head and accumulate from the nearest store in their location. Even returning through this channel is more convenient to the consumer. So, they could without difficulty engage with product and can take advantage.

Augmented Reality will also beautify the shopping experiences. It becomes the boon in destiny. Whether used to try beauty products and clothing on-line, in a mall or in a shop’s mirror or to play a game to unlock some discounts, AR engages customers in new and interesting ways. Data analytics might be used to gain and retain customers with the use of AI and this will be the differentiating component.

Employing artificial intelligence and machine learning will be imperative to increase sales.

Whether to book a rental car, discover the great deal, or automatically re-order supplies, customers will depend upon AI to manipulate their lives. Retailers are already using machine learning for higher focused and improved targeting.

So those technology and effective operation will lead to higher success in retail industry.

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How does IKEA Do It?

Nishu Kumari Kejriwal (MBA 2019-21)

To create a better everyday life by providing good home furnishing for people belonging to any class is the Vision of IKEA. IKEA is a Swedish-founded multinational group which is owned by INGKA Foundation and not listed on any of the Stock Exchanges. This is a purposely formulated strategic decision as being a company owned by a charitable trust, it enjoys taxation benefits as well as prevents hostile takeovers.

IKEA is one-of-a-kind furniture retailer. They have more than 400 giant stores which attracts 900+ million visits in the whole world. They can be easily differentiated from any other furniture dealer. If you ever got a chance to visit an IKEA store, you must be familiar with their layout which is a combination of Warehouse and the store itself as one entity. They offer quality furniture at affordable prices. Their key strategy which contradicts from other competitors is that they spend less money to increase sales. They aim to minimize their labour costs, use resources sustainably and increase their productivity by shifting service activities to their customers itself.

If you like furniture at IKEA, you need to work for it. From the tag attached to the showcased model, you need to write information about it on a paper and then locate this furniture in their warehouse using that information yourself and load it in a trolley. The last step would be to wait in the checkout line to buy it. Moreover, if you have bought any fragile material, then they have a self-wrapping area too.

One might think why to go to a store where a customer needs to make efforts to buy the product. The key advantage that IKEA provides to its customers is that they offer affordable quality furniture along with a customization option as per their individual preferences. Their official website is thisismykea.com where anyone can customize furniture online.

To achieve quality at affordable prices, IKEA optimizes the entire value supply chain by emphasizing on building long-term supplier partnership and investing in highly automated and mass production. They tend to save money from efficient supply chain which in turn decreases the cost of production thereby saving their customers a lot of money too. They spend no money on fancy packaging, thus using plain flat brown boxes for transportation.

These containers are sent directly from factories to stores to ensure reduction in use of fuel.

IKEA redesigns packaging every time to make sure that no bit of space is left unutilized while transportation. They believe transporting furniture in bits and pieces would double the 10|K A I Z E N ’ S O P E R A T I O N S & R E S E A R C H E N T I T Y

efficiency by affixing them as per consumer preferences and reducing carbon emission by making fewer trips from warehouses to stores. Hence, they offer furniture which are cheaper to manufacture with wide variety and no assembly costs. When it comes to using resources sustainably, IKEA never fails to surprise us. It uses left over materials from one product for making of another one.

You might be amazed to know that IKEA earns a significant portion of their revenues through psychological tactics. Any person spends an average of three to four hours in an IKEA store. Since an IKEA store is usually located far away from the cities, IKEA restaurants came into picture. These restaurants are made inside the premises and don’t require the customers to go out for food. The tactic here is that the food available is of very minimal price. A frozen yogurt ice cream for 1$ tricks the customers into thinking that the sofa set available for 800$ is also economical and pocket-friendly. Another strategy is the layout of these stores. An IKEA store is a bunch of little different sections carefully constructed together like a maze with only one exit at the end. After picking your favourite furniture, this layout makes you walk through the entire maze displaying all of their products.

Consequently, many people forget about the exit and end up picking stuffs they weren’t planning to.

When it comes to giving back to the society, IKEA is a step ahead. They have taken steps to manage their external resources to achieve long-term goals. Being a furniture company in such a large scale, it uses a lot of wood leading to deforestation, but they have pledged to grow at least as much wood as they use by 2020. Millions of trees have already been planted

by IKEA as of now.

The way in which IKEA maintains a good partnership with its customers is also very appreciable. People from IKEA go and visit homes all around the world. They talk with people, look for their closets, and measure their cabinets and so on. This serves as a starting point for them to develop products of different designs and create home furnishing solutions.

They believe having one-to-one conversations with people gives them valuable insights and advocates continuous refinement of production and distribution. They are never satisfied and constantly look for new and better ways of doing things. Their business model proves that by getting a little creative and innovative with a few of the various factors involved in a supply chain, one could go a long way. IKEA has a passion for life at home. It comprises of individuals from all over the world united by a shared vision and values that they believe are more relevant today than ever before.

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Formula One: The Race Behind the Race Aamenah Khan (MBA 2019-21)

Formula 1 is the highest level a driver can reach in motor racing under a Single-seater class.

This is one of the most popular motorsports in the world. It has a number of big sponsors, design the fastest cars, latest technology and teams that are constantly innovating. The season lasts for 9 months of year with 10 teams, 20 cars and 21 races across 5 continents.

This fast paced, glamorous sport has operations that take place behind the scenes and the complex logistics involved in every team. To get an idea of what the logistics in F1 involves we will take a team for example. Each team has two drivers and a car each for the said drivers. Apart from these, all the equipment, tools, fuel, computers and technology related equipment and even food need to be transported for each team. After the race day on Sunday each team has to pack up and start moving everything to the next race location where the team has to be completely set up by Thursday in time for the beginning of the next race. The race calendar usually gives the teams enough time to take care of the logistics but once in a while it can be consecutive weekends. The entire process is planned out to the minute details and executed with precision that makes the logistics as quick and smooth as the race itself.

DHL is the Official Logistics Partner of Formula 1. The DHL Motorsports team has 35 years of experience in handling the complete logistics behind F1. They need to move approximately 2000 tons of cargo around the world to different race locations. There are 3 modes of transport used by the teams- land, air and sea.

The Land aspect- roadways- come to the maximum use during the European races. Since all the teams have headquarters in Europe they can pack their equipment and cars in trucks which easily travel across the continent. The team removes parts of the car which are delicate like the front and back wings, and engines. The cars are elevated and kept in the trucks.

Everything else is loaded keeping in mind maximum space utilization for all modes of transport. This is kept in mind and usually they have cargo crates which are designed to fill up the space available in the hold.

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Air and sea travel is used extensively and made use for ‘flyaway races’- these are international races that take place outside Europe. They divide the content according to delicates. There are two categories- critical and non-critical.

The critical contents are sent as air freight and this includes electronics and IT, two race cars, chassis, bodywork and wheel rims. The non-critical contents are for shipment and include all of the garage. The huge containers take up space beneath the deck. These shipments leave 4-6 weeks in advance to reach the race location in time. The same for air freight- the cargo boxes are optimally made to fit the fuselage to have the maximum space possible. The cars have their own packaging as well as the wings of the car to keep it from moving. This cargo set is called a kit. Each team has multiple kits which move to various locations to save time.

The team headquarters plan these shipments to cover two international locations. The kits move to the first four races for use and after this are packed up and shipped to a different flyaway race. Some locations get their own kits from headquarters and the others are returned back home. All engines are provided by the respective companies which are associated with the teams and tyres are supplied by Pirelli. These companies handle the shipping to each location themselves for every team.

Logistics in F1 are complex and require a highly skilled workforce and precision planning to have a successful race weekend. After many years of championships and race weekends, the teams are capable of handling these situations with efficiency. The entire race weekend depends in part on these processes that take place. Ensuring that the cargo reaches each destination is beyond imperative to every team. Formula 1 is such a sport where each cog in the system is essential to the whole, each person has a responsibility for his/her part. Every member can do their role with detailed rigour after years of experience. This makes it easy for teams to know for sure that their cargo will be at the right place, at the right time.

Through this we can observe that operations management in any sector or business can make or break a business. Logistics is a building block of businesses by establishing a platform for enhanced performance mechanisms to function seamlessly.

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Tourism Industry- A Reality Check Aayush Jain (MBA 2019-21)

Tourism is of the biggest industries, and also one of the most complex one. Mostly businesses operate with a long and complex supply chain, comprising a number of different operators, reducing the influence of each individual business. • Customer demands are evolving rapidly, so tourism businesses must also operate transparency. World is now in an era of greater instability, politically and in terms of environmental and social risks.

The supply side of the tourism industry has been largely ignored whereas emphasis has been given to promotional and marketing activities. It’s not unique for tourism industry as per research most of the service industries focuses on marketing and distribution activities. The industry needs to be analysed from an integrated (supply chain management) point of view.

In tourism industry push strategy is given emphasis the production of a product is authorized based on demand forecasting of customer purchases.

Inventory management in tourism industry is also complex because relatively high fixed cost which are paid in advance whereas variable cost is low which makes it difficult for the tourism managers to balance supply and demand in the short run by varying production capacity.

Supply Chain Management aims to satisfy customer needs at the right time with the right products, so product development plays a vital role in supply chain. But it is relatively neglected in tourism industry due to its composite nature. There has been very little analysis of tourism product development, in comparison to the research efforts directed toward tourism marketing.

Also there are problems due to lack of information technology in the tourism sector such as increased operating cost, decision errors, service failure and weakened relationships Tourism is a coordination intensive industry in which different service are grouped together to form a final tourism product. To maintain competitive advantage over rivals many tourism firms have already adopted coordination strategies. Coordination occurs between service providers such as hotels and airlines, and tour operators and travel agencies, within the same echelon and/or among different echelons for example major European tourism firms are already integrated with flights, hotels and other travel intermediaries. Today the supply chain 14|K A I Z E N ’ S O P E R A T I O N S & R E S E A R C H E N T I T Y

needs to be fully integrated so that there are no conflicting objectives between different operators in a supply chain.

According to relationship commitment-trust theory, shared values, relationship commitment and communication are important factors when achieving collaborative relationships so all these factors are also important for successful tourism supply chain.

Thomas Cook Group was a British global travel group. It came into existence on 19 June 2007 by the merger of Thomas Cook AG and MyTravel Group. Thomas Cook Group operated in two separate segments i.e.: a tour operator and an airline. On 23 September 2019 Thomas Cook went into compulsory liquidation. It was listed on both London Stock Exchange and Frankfurt Stock Exchange. Due to their announcement of liquidation about Twenty-one thousand worldwide employees were left without job and Six lakhs customers were left abroad resulting in the UK's largest peacetime repatriation.

The group funder’s: Royal Bank of Scotland Group and Halifax that the group should be recapitalised so that sufficient capital is available with the group for efficient operation of the group till January when bookers for the tickets are comparatively low and less chance of getting liquidated. Such request meant that group needed additional two hundred million Euros, but the efforts for raising funds got in vain and on non-payment of airport charges on 23 September, 2019 Civil Aviation Authority announced that Thomas Cook Group opting for liquidation. After the announcement over Forty employers with more than six thousand vacancies were on hand to speak to potential candidates about their career option and next jobs. On the feedback many said such event helped them out.

As per the critics the reason behind the Thomas Cook crisis is disastrous merger in 2007, ballooning debts and the internet revolution in the tourism sector which allowed customers to use web services rather than opting travel agencies, and the continued Brexit uncertainty resulted in the collapse of the legacy of hundred and seventy-eight years’ company. As per reports its not that British have stopped taking holidays, it’s the change in way the take holidays, with the number of city breaks now, outstripping beach holidays. In today’s “Information Techy” world one out of seven people opt for high street travel agency to buy a holiday (as per reports of Abta). Their hotel business was harmed due to the customer shift to Airbnb, EasyJet, Ryanair.

The one of the biggest competitor of Thomas Cook, Anglo-German group Tui has also suffered the same trend but is standing strong still due to certain factors such as less debts, owning its own hotel and cruise ships.

Today, the tourism sector needs to retrospect and analyse again, they need unique strategy to outshine by integrating between operators in the supply chain and focusing on product and the quality rather than its marketing. Products need to be of high level and at completive price. The travelling agency needs to develop their PODs to survive in the market.

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Role Of Data Analytics In Improving Operations Tanmay Choudhary (MBA 2019-21)

Most of the businesses in today’s world are turning to data analytics to provide insight when making operational decisions. There are two particular areas of specializations where data analytics can help companies: improved service delivery to its customers and more efficient and effective resource allocation. In order to arrive at actionable insights, the analysis relies on multiple data sets of varying size and content. We will be discussing one simple example where data engineering, data analysis, and the merging of two data sets can help a company in both the above areas.

Most of the companies provide ongoing support for their products and services. This support often have the requirement of around-the-clock support from a team of technicians and engineers who can quickly respond to issues as they arise. The usage of product by the customer and their geographic locations varies, it may be difficult to appropriately schedule support staff across a 24-hour period, leading to the possibility of over- or under-staffing during any given period. Taking appropriate support-staffing decisions is critical to the two operations are as noted above. Understaffing leads to delayed response times hence reducing the quality of customer service, while overstaffing indicates that resources are being underutilized, adding unnecessary costs.

The conventional approach towards staffing decisions involves estimating the baseline productivity of a single staff member that is how many number of responses can a staff member respond to in a given period of time, and identifying any temporal patterns to when responses are generated that is how the request generation rate differs by hour-of-day or dayof-week. However, these metrics can be difficult to determine without complex data analysis, and using them in a straightforward way may require making several simplifications and assumptions. An advanced and alternative approach discussed below, is to examine patterns in the metric of interest and make scheduling adjustments based on that metric.

Request ID RQT101

Time April 4, 2016 01:03PM GMT

RQT101 RQT102

April 4, 2016 01:06PM GMT April 4, 2016 01:13PM GMT

Action Created Modified by Technician Created

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RQT103

April 4, 2016 01:14PM GMT

RQT102 RQT104

April 4, 2016 01:17PM GMT April 4, 2016 01:17PM GMT

RQT104 RQT105 RQT106

April 4, 2016 01:21PM GMT April 4, 2016 01:22PM GMT April 4, 2016 01:22PM GMT

Created Modified by Technician Created Modified by Technician Created Created

The modern approach

The around-the-clock customer support, a good metric for support staff responsiveness is the amount of time it takes for a support technician to take a first action in response to a service request. We are imagining that issues or service requests are raised through a software interface that generates a service request and that the entire service team has the ability to respond to request in the service queue. The goal of the analysis, then, is to understand how this metric varies by staffing level and determine if any adjustments are required to be made. .

Preparing the Data

For a software requesting system like the one described above, service responds may be stored in a historical time series that produces a record each time an action related to the request is taken. If the data are stored in a relational system, these historical records may also connect to metadata related to the request, like the entity that opened the request and further details about the request. Irrespective of the complexity of the database, however, it should be possible to join and query the database system to obtain a single, time series table where each record contains the following information: request ID number, time of action, and action taken. It depends on the specific problem, there may be important metadata that should be included to further segment the data, like the type of request, but for this example we will assume the simplest case where all request types can be treated the same. Below table shows a sample of what such a time series table might look like.

Using these data, we can derive another data set that gives the amount of time elapsed between when a request is created and the time of first action. These derived data (sample shown below) will serve as the basis for our analysis.

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Request ID RQT101 RQT102 RQT103 RQT104 RQT105 RQT106

Time Created April 4, 2016 01:03PM GMT April 4, 2016 01:13PM GMT April 4, 2016 01:14PM GMT April 4, 2016 01:17PM GMT April 4, 2016 01:22PM GMT April 4, 2016 01:22PM GMT

Time to First Action (Min) 3 4 10 4 5 6

Aggregating the Data Aggregation of these data is done in several ways to obtain useful insights into support operations. The answer of the initial question we posed about whether support staffing levels are adequate, we would aggregate the data by determining the average time to first action for requests created during each hour-of-day. Since staffing schedules may change periodically, often on a monthly basis, we also limit the analysis to requests created during the specific period of time when a particular schedule was in effect.

This plot below shows the average initial response time by hour-of-day that a request was created in red. For comparison, we also show the average number of tasks opened by hour-ofday in blue. The black dashed line shows the number of support staff working during each hour-of-day. Perhaps the most striking feature of this plot is that large increase in response time for requests opened between 16h-19h (4pm-7pm). This increase also coincides with a drop in staffing levels from 3 people to 1 person.

The immediate implication, based on a qualitative visual examination of the chart above alone, is that staffing levels should be increased during the 16h-19h period.

But let’s examine this in a more quantitative manner….

Initial Response Time vs. Request Creation Rate We might expect there to be a relationship between the average initial response time and the average numbers of tasks that are generated at any particular time. The plot below shows, for each hour-of-day, the average response time compared to the average number of requests created as green dots. The black dashed line shows a linear fit to these data used to determine if there is a trend in this relationship. Once we remove the significant outlier corresponding to the 18h-19h period, we get the trend shown in the solid black line.

Comparing the Root-Mean-Square Error (RMSE) calculated after removing the outlying point for either fit does not indicate a substantial difference (1.4 vs 1.5), and it’s also apparent by visual inspection that neither fit provides much predictive value. For example, based on the fit alone, we might expect that at no request creation rate below 4 requests should we expect the initial response time to exceed 5 minutes, but the data show 5 hours-of-day when the response time is greater than 5 minutes.

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Initial Response Time vs. Staffing Level Another relationship we should examine is between the staffing level and the average initial response time. The plot below indicates a more apparent trend where the higher the staffing level, the shorter the initial response time. For each hour-of-day, the blue dots show the average response time for any given staffing level. Once again we perform a simple linear fit to the data with (dashed black line) and without (solid black line) the outlier corresponding to the 18h-19h block.

In this case, removing the outlier does have a significant impact on the trend line, though the predictive values of both fits are similar. To use the example above, both fits would suggest that keeping the minimum staff level at 3 people or higher would result in an average initial response time below 5 minutes. There are only two hours-of-day where these models are incorrect (11h-12h and 13h-14h), and in both of those cases the average response time is still below 6 minutes.

Given this trend, the longer initial response time during the 18h-19h block is less surprising, though this hour remains a significant outlier. To better understand this, we can go back to our initial plot which showed the data as a time series. When we do so, we can see that the increase in initial response time occurs during the final hour of a 3 hour block where there is only 1 person staffed. Analysis of additional data concerning the other duties the support staff are attending to may offer better insight into this outlier. Initial hypotheses, though, could be that either the staff member on duty begins to feel fatigue during their third hour alone, slowing down their overall performance or developing a backlog of work due to competing responsibilities, which slows down initial response time.

The analyses we have already discussed above, however, suggest that to make an improved staffing decision the support operations manager does not need to understand the cause for the 18h-19h block outlier. Increasing the staffing level to 2 or 3 people during this period is likely to reduce the initial response time. If the manager sets an initial response time target of around 5 minutes, these analyses also suggest that the team is overstaffed during the 1h – 8h block when there are 4 or 5 staff members on duty. Rescheduling these staff to later parts of the day will likely reduce the average initial response time overall and significantly improve the response time during the 16h-19h block.

Conclusion It’s clear data analytics offer powerful tools for helping a company make better operations decisions. In particular, combining data from multiple sources and applying time-series techniques can provide deep insights into a company’s operational strengths and weaknesses.

In this blog post, we have shown how combining straightforward analyses of a company’s request management data with information about its staffing scheduling enables a support operations manager make better staff scheduling decisions, improving customer service and reducing overhead costs..

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