PreCOVID-19 to COVID-19 to PostCOVID-19 dilemma for CIOs and Wayout

From last 4 months we have seen that COVID-19 has turned the wheels of industry in the direction which was not anticipated by many. Many corporations have changed or have been forced to change the way they are looking at business or the way they are executing business. Since there is no vaccine or cure available as of today, the actions taken by individuals, corporations as well as governments are towards prevention which has impacted the whole fabric of personal and professional life. It has changed the manner in which basic things are done e.g. we no more shake hands when we meet or we do not come within perimeter of 6 ft from other person, we cannot go out and eat, we prefer ordering even groceries and veggies online rather than going out and choosing ourselves, guests are not welcome, we are afraid of travel, large RFPs are submitted, presented, awarded without an in person meeting, I can go on and on. Smart businesses have created mechanisms to handle this anxiety in the minds of customer and developed incentives like free and safe home delivery to promote the same and offset the downside created by odd customer behavior. Most of the businesses are suffering due to lack of customers coupled with lack of intent of buying not-so-essential things from customer. Customer also has learnt to live with different kind of processes where everything happens from home, most of the stuff is bought online, people have started planning for groceries and essentials which might not be available easily, it has gone to a level where in disturbance from kid in a professional meeting is accepted. Scientists are working hard, and they will definitely find some vaccine and / or cure for this virus. Just that we do not know when. When they find the cure will everything return back to the old glory or there will be a new way. Everyone kind of believes that it will not be the old way but there will be a new normal that we will need to deal with.

• Do we know what is this new normal? – No
• Do we know if this new normal will be same for all? – We know that it will not be same for all, but we do not know how it will differ

If we look at situation in which most of the CIOs are today, no one envies it.

•  They have to ensure that the business runs with whatever constraints have been enforced,
•  They have to ensure that the business runs even with the new way of business transactions (which is evolving as the COVID -19 situation is unfolding) by building new applications or modifying existing applications,
•   They have to ensure that IT environment secure from all the predators
•   They have to conserve the cash, forcing them to make difficult decisions like closing/postponing noncritical running projects, reducing IT team with no fault of theirs (with a knowledge that they will need them back soon enough and may not get them back) etc.

This is not all, the CIOs have to be ready to zoom in to high gear as soon as a solution for COVID-19 situation is found. Business teams will assess the situation and determine strategy adjusting to new normal and recovering all the losses that it encountered during the crisis. They would expect every department in the organization to step up and do their best. CIO will be expected to work in tandem and get the IT systems ready for the new normal almost in parallel to the realization of new normal. This is tough as new normal will comprise significant online/automation component and IT has to play a major role in it. With all these uncertainties and moving parts, CIOs are in dilemma as to what to do, when to do and how to do? There is no case study nor there is any template and they have to find their unique way out.

I think, Differentiated Needs Pyramid, if applied to the three situations i.e. PreCOVID-19, During COVID-19 and PostCOVID-19, CIOs can find a way out to bring in some proactive measures and partner with business to get it back on track as fast as possible. 

In my earlier blog, Predictable Customer (Internal) Experience Improvement- CIO Perspective  

 https://personalandprofessionalexcellence.blogspot.com/2019/09/predictable-customer-internal.html,  We have seen that a CIO can be successful in improving the experience that they are providing to their customers i.e. Business Leaders by understanding their needs better. Following picture depicts the differentiated needs of the Business Leaders in the business as usual (PreCOVID-19) situation.

This is a five level Differentiated Needs Pyramid and once CIO is able to identify specific needs for the each level for Business Leaders corresponding to their business, then they can take up the right initiatives and go beyond the expectations from business and be a partner to business in its growth. 

If we extend the same philosophy a bit further and analyze this pyramid for three situations i.e. PreCOVID-19, During COVID-19 and PostCOVID-19, we can see how the needs of Business Leaders are going to change at each level in each phase. Using this, CIOs can predict what is going to come their way and they can start addressing the same. Following diagram provide the glimpse of how the needs are likely to be in these three situations Each CIO can plot the 5 levels of specific needs for their business leaders using needs of their specific business.

Each business is unique and their strategy to woo their customers is unique. This needs to be considered while detailing out the actions under each level that might be required to be taken by CIOs in order to satisfy or exceed the needs of their customers i.e. Business Leaders. If a similar exercise is undertaken by Business leaders for their end customers, they will know how the needs of their end customers are changing, thus what strategies need to be adopted by business to satisfy their needs. 

In my earlier blog Predictability in Customer Experience Improvement – A Perspective for Grocery Retail Industry,

 https://personalandprofessionalexcellence.blogspot.com/2019/07/predictability-in-customer-experience.html?_sm_au_=iVV4Rtj4p0NLfDVr  I had taken an example of Grocery Retail scenario for two segments of customer i.e. Customers with age greater than 50 & customers with age below 30. It was clear that the needs vary at each level and the business leaders assess them for specific customer base to determine specific initiatives for creating stickiness. I have extended the same example for customers with age greater than 50 and created a scenario of three stages PreCOVID-19, DuringCOVID-19 and PostCOVID-19. We see a significant swing in the needs as we transition. Some changes made during COVID-19 phase do stick around or get a little modified and get added to the PreCOVID-19 scenario to give a unique set of needs at different levels to the customer base. The diagram below provides a glimpse at this. Certain things like Online Ordering, Free Home delivery, Easy Curbside delivery, Security, pop up at multiple places, which means business will need to extend and enhance the model they have created during COVID-19 and make  

available to customer. The only change would be it will not be a compulsion on consumer to use this facility, but it will be an additional perk that consumer can avail. Better cost-effective way to create this facility through an IT project would definitely be on card for such an organization. Another situation could be around delivery; free home delivery or same day delivery or same day curbside pick up would be expected and if CIO can create an application which will help Supply chain team to make it happen, the business leaders would love it. During COVID-19 consumers were ready to bear some hardship due to fear and desperation, however in PostCOVID-19 scenario, they would not be ready for hardship and will expect the same facilities without hardship and additional cost. The race would be to satisfy these new needs (New Normal) and win over more customers and higher business.

In Summary, the transition from PreCOVID-19 to COVID-19 to PostCOVID-19 is dramatic. Consumer behavior will change almost 180^o each phase. A new normal will be attained in a short period after the solution to COVID-19 problem is found. There will be race to understand this new normal and satisfy the needs of customers in this new normal so that business can get itself back on track. The level of uncertainty is preventing business and their IT teams from launching new initiatives. In this situation Differentiated Needs Pyramid can help Business and IT to proactively look at what could be possible areas that they should work on and be ahead in the game.

Customer Experience – Perception or Reality

Customer experience is the frontier where the battle for customer loyalty (and associated revenue) is being fought. Every industry and companies therein have started focusing on it. New ways and methods are being experimented regularly. Companies are trying to give a better customer experience than what they are offering today or what their competitors are offering. This is to create a unique differentiation and create a challenge to its competitors.  The game is to give customers something beyond their expectation in every transaction that happens between company and customer. Key is to understand the expectations, which do change based on the situation, and provide a right response at right time. 

Gartner has defined Customer Experience as the customer's perceptions and related feelings caused by the one-off and cumulative effect of interactions with a supplier's employees, systems, channels or products.  As per Forrester, Customer Experience is, how customers perceive their interactions with your company.

Note the word perception used in both the definitions. Perception, according to Cambridge dictionary, is a thought, belief, or opinion, often held by many people and based on appearances. Which means customer experience is totally dependent on how a specific customer feels specifically about a specific thing during the interaction. It may not be reality and different customers will have different experiences for the same interaction and totally governed by the psyche of the customer at that moment. Theoretically the same customer can experience different experience for the exact same interactions at two different times. If Customer Experience is a perception, a few questions arise

·       Is there any Base line or Absolute reality or Empirical Gold standard for Customer Experience which can be used by companies?

·       Is there any way to measure perceptions?

·       Perceptions can change based on various extraneous factors on which company has no control: in that case, is this a valid measure or we need to find a better way to understand the perceptions quantitatively?

Customer experience is subjective and hence measured in generic terms like Bad-Good-Superlative or on the scale of 1-5, etc. i.e Customer experience is a result of interaction between the response a customer gets throughout the transaction to procure any product/service vis-à-vis the expectations he/she has, before starting the transaction. If the response matches the expectations, customer typically brands it as a “GOOD Experience”, if expectations are not met, the experience varies on the negative side and if customer gets something beyond what is expected, the experience gets labeled as SUPERLATIVE. This brings out another variable which impacts Customer Experience i.e. “expectation of the customer from the transaction”. This impacts the score given by customer. In the normal circumstances, current experience becomes baseline expectation for the next transaction and so on. The same level of interaction creates -ve impact on Customer Experience levels as the +ve gap between current experience and expectation is reduced and over a period of time, it becomes zero or -ve, turning the direction of Customer Experience in opposite direction.

Although Customer Experience is a perception of customer and it can be different for different customers, customers take their actions like buying more or shifting to competitor based on these perceptions. So, these perceptions become reality for the company, and they need to act as if they are absolute reality. Hence Customer experience could be defined as REALITY OF PERCEPTION

This subjectivity and variability create a significant challenge for companies. It is difficult to quantify the Customer Experience level for any specific transaction with customers thus posing further challenges in identifying the remedial measures as well as implementing them to improve the CX. This is one of the key reasons why companies are hesitant to implement new measures and unsure of their results. If we are able to remove the subjectivity from the Customer Experience measurement, the companies can heave a sigh of relief. I have an idea to achieve this and converting Customer Experience from Perception to Reality which can be quantified. The key is to use the available data in the system rather than asking feedback through a survey (which adds subjectivity). We can define success criteria for any transaction e.g. If we are organizing an event in the store, success criteria of the event could be increase in footfalls into specific zone in the store. If we are able to count footfalls at the event, footfalls at the target zone when the event is on and compare the same to the footfalls before the event was launched we can find if the event was effective and customers liked it or not without asking the customers. If the footfalls are more than the normal footfalls, the event is effective; if they are same then event has no impact and if they are reduced, then event has -ve impact. These measurements can be taken on continuous basis and company can tweak the event on continuous basis till they get the right result. The example given above is a simplistic example to get an understanding of concept of quantification of Customer Experience without asking customer. With new developments in AI/ML, several algorithms could be written to understand complex situation.

Once we are able to quantify the Customer Experience using available data (not using survey), it could be rationalized across multiple segments, zones, geographies, etc. and company can take appropriate actions. It is now no more Reality of Perception but Reality of Reality.  

Customer Experience Measurement – Past data or Future (Predicted) data

In the last couple of blogs, we discussed about the three key questions an organization needs to answer to bring in clarity in its CX improvement program as well as assessing and enhancing benefits from the same. These are, 

1. Should Customer experience be measured as stand-alone value or it should be measured in terms of  rate of change in the CX measure? 
2. Should we measure using Direct Customer Feedback or through Indirect (derived) feedback? 
3. Should we use past data or future (Predicted) data?

We deliberated first two questions in the earlier blogs and will discuss the third one in this blog. Refer following links to read through-          https://personalandprofessionalexcellence.blogspot.com/2019/11/customer-experience-measurement-stand.html,

https://personalandprofessionalexcellence.blogspot.com/2019/11/customer-experience-measurement-direct.html

This blog talks about the third question regarding usage of “past” or “future data (predictions)” in order to bring about business improvement using CX. Before we get into the discussion around data and its state, let us look at the typical process of CX measurement and how it helps in business improvements.

Following diagram depicts the process in simple terms.

Organization assesses customer journey for a specific aspect of business and identifies areas where an intervention for improving CX is necessary. It then designs and implements the intervention based on the findings from journey assessment as well as its understanding of customer preferences & behavior. Feedback from the customer is collected through survey / interviews using online / in-person mechanism. If the feedback is positive i.e. CX is good, then organization continues the journey to reap benefits of the intervention. However, if the feedback is mixed or not encouraging or there is no impact at all; organization identifies shortcomings/misses during design / implementation of the intervention and subsequently defines a tweak that would be necessary to address the same. This tweaked intervention is again implemented, and the same cycle follows. If the mistake is such that it cannot be corrected by smaller tweaks in the intervention, then organization abandons the initiative as early as possible to contain the damage it might be creating. The cycle from assessing the feedback till implementation of tweaked intervention easily takes 2-4 months. If the right fix requires more than one tweak, the delay in getting the desired results increases proportionately.  

As we know, CX (as well as related revenue impact) follows a lifecycle similar to product lifecycle as shown in the following diagram. Refer following link to understand detailed discussion around CX lifecycle.   https://personalandprofessionalexcellence.blogspot.com/2019/07/cx-life-cycle-management-for-continuous.html  Once the CX intervention is correctly designed and implemented, it starts showing positive results on experience as well as revenue as shown in the diagram. However, if the intervention is not appropriately designed and customers do not embrace it as expected, the tweak cycle kicks in. After one or two tweaks the CX journey settles in. In such cases the graph for CX shifts to the right (Blue Line in the diagram below) creating a period of uncertainty from the start of first intervention to the implementation of intervention after tweak/s. 

During this period, CX may go down or waiver or may not change at all. The company is busy in finding the right tweak and can be vulnerable for attacks from competition. There are chances that it may lose revenue as well as goodwill with customer base.

There are two challenges faced by company in this endeavor. First one is feedback cycle takes significant time delaying the tweak that might be required to be implemented.  Process of getting feedback from customer has inherent limitations in terms of how frequently you can go to customer and ask their feedback coupled with no guarantee that customer will provide feedback when reached through modes like e-mail or online survey. Organization is pushed into uncertainty zone and there is no easy way to reduce this time. This limitation could be eliminated to some extent by creating multiple sets of customer segment with similar characteristics and reaching out to them at higher frequency; however, the process becomes complicated and does not help reducing uncertainty period by significant proportion.

Second challenge is that we really do not know when the CX lifecycle attains maturity. The trajectory is known but the time period for each zone like growth or maturity is not known and it changes with the specific intervention and its impact. It could be a steep curve up and steep down or it could be slow up and steep downward or it could be steep up and slow down. It is critical for a company to understand the stage of lifecycle CX is passing through. If the CX is in upward climb, organization continues to reap in benefits from the intervention whereas if it is on the downward slope, the organization starts reducing the benefits that it receives through this intervention and may start losing revenue. Organizations wish to elongate the growth stage as long as possible and would like to be in maturity stage forever. However, in reality this does not happen, the impact of the CX intervention weans away at some point of time and CX graph enters in to decline phase. It is critical for organization to plan another tweak or new intervention right in time so that its impact starts showing up by the time the impact from earlier intervention gets in to decline mode. The organization struggles to find this point, it cannot estimate the time it is going to take for any intervention to reach this maturity/decline inflection point (CX fatigue). It is also difficult to measure the CX level continuously to track its progress and estimate the next intervention point leaving organization vulnerable.  

Can we overcome these challenges? – YES we can !!!

The problem could be solved if the organization uses future (predicted) data. Organization can construct a model using indirect feedback mechanism as described in the earlier blog. This model will enable organization to obtain the exact stage of CX at desired frequency like daily. It can also go to a hourly frequency if we have the right model with right parameters and technological capability to manipulate the data collected through these points.

If organization creates a model using various data points from different interventions which depict the life cycle pattern for an initiative and build a capability to self-learn; this could create a tremendous intelligence for the organization to predict what is going to happen in near as well as distant future and when it should be ready for next intervention. The customer behavior is unpredictable and CX movement may not be same as what is predicted or there could be a significant campaign run by competition which is impacting the CX behavior; the organization can get a sense of these movements from the capture of indirect feedback without really waiting for physical feedback and can adjust the projections accordingly. This generates new predictions for organization to re-calibrate their actions on real time basis. The predictions are dependent on the AI/ML based self-learning model. The closer it reflects the reality as well as its ability of mid course correction determines the effectiveness.

In summary

• Mapping the CX value v/s Rate of change of CX can provide the status of CX initiative and direction that an organization should take going forward
• The indirect method to capture CX using parameters available in the organizations business systems wins over the direct data collection mechanisms
• Predicted data can provide organization with inputs which are early and granular than the past data collected from the customers
• The success of the CX backed business improvement depends largely on ability to create the algorithm which could represent the customer behavior using the parameters available for us in the system as well as one for predicting the CX lifecycle. AI/ML can enable organizations to achieve this and can help move ahead of curve in continuously improving CX as well as improving the growth rate for the business.

Customer Experience Measurement – Direct v/s Indirect

In my last blog, we discussed about three key questions an organization needs to answer to bring in clarity in their CX improvement program as well as assessing the benefits from the same. These are,

1. Should Customer experience be measured as stand-alone value or it should be measured in terms of “rate of change” in the CX measure?
2. Should we measure CX using Direct Customer Feedback or through Indirect (Derived) feedback?
3. Should we use past data or future (predicted) data?

We deliberated on whether we should measure the CX in a stand-alone manner or using “rate of change” in my earlier blog and concluded that measuring the “rate of change” will benefit the organization more. It will also help to assess the stage of the CX lifecycle the initiative is passing through and take the appropriate action. You can read the same using this URL--  https://personalandprofessionalexcellence.blogspot.com/2019/11/customer-experience-measurement-stand.html

In this blog, I am going to discuss the second Question i.e. Should we measure CX through Direct Customer Feedback or through Indirect (derived) feedback? First let us understand what we mean by Direct as well as Indirect

Direct Feedback: When a feedback about customer experience is obtained directly from a customer through any kind of Q&A mechanism, it is called a direct feedback. The mechanism could be a physical survey, online survey, meet & greet meetings, telephone, home visits, etc.  We ask customer to rate the product or service and their rating decides the CX level.

Indirect (Derived) Feedback: Indirect Customer feedback is calculated by establishing a relationship between multiple parameters, other than answers from customer and available through customer transactions. Multiple parameters like sale of a specific product before and after the initiative is launched or changes in the traffic on website or customer behavior on website or customer response in various geographies, etc. which are available with the organization can be used to create an algorithm which could represent the pattern of CX behavior and used for measuring the status of CX at any point of time. 

Following table provides a comparison between the two methods on certain criteria which can throw some light on pros and cons of both the methods

	Direct Feedback	Indirect (Derived) Feedback
Customer Involvement	Real feedback through multiple means of interviewing / Survey	Feedback interpretation depends on the definition of relationship between the parameters measured and customer experience. Experimentation is required to build the relationship between multiple parameters and CX
Ease of gathering information	Process of gathering & analyzing feedback is predominantly manual or semi-automatic. Thus, requires longer time	No special information gathering is required. Existing information is used. So, process could be completely automatic
Frequency for measurement of CX	Limitation on how frequently you can go to a customer and reluctance of customer to give feedback frequently.	No limitations and every transaction could be used for calculating CX. The measurement could be near real time.
Coverage – Customers	Due to inherent nature of the process, there is a limitation on how many customers could be contacted and how many really respond. Many times unhappy customers voice their feedback and happy customer do not respond creating incorrect picture.	No limitations, feedback calculation can consider every transaction
Coverage – Bias in selection of respondents	Due to limitations on reaching customers, there is a possibility of introducing a bias in selection of customers to provide feedback and thus influencing the CX	No bias as entire data can be used to give real picture.
Coverage – Time period	Due to longer frequency, the information gathered does not represent the experience for the whole period but typically for the events / transactions just before the survey.	As the data is used continuously, a true overall picture for the respective time period can be achieved
Coverage - Customers / Non-Customers	Typically, the customers who have bought products / services are part of this exercise and customers who have not bought the products / services are not. As a result, we tend to miss out on the experience traits which have made some customer to go away from our products / services	The indirect mode enables us to compile data for those who have not bought the product / services through some of the parameters like "Returns", "Selection of items and removing from shopping cart without a purchase", "Complaints", "Replacements", "footfalls v/s sales", "termination of services", etc. This information is available and could be used for building CX model.
Response time for CX feedback	Understanding CX, deciding action based on it, implementing the same and measuring the impact is a very long process and could easily take 2-3 quarters if not more. It takes time to detect negative trend.	The CX could be measured on a continuous basis. The frequency could be daily or better depending on the algorithm and data collection & crunching capability. Company can get the trend in CX as it is taking place and empowers it to tweak the CX intervention based on the same real time. Negative trend could be tracked early.

Based on the above table, it is evident that indirect method wins the game. Only challenge here is to get the algorithm right. Unless we get the algorithm right, all the measurement is of no use and can lead us to wrong direction. So if the organization can use new techniques in AI/ML to create a self learning algorithm using the past data along with experimentation; organization can really go ahead of curve in continuously improving CX.

Ref :    

•  CX Life cycle management for continuous improvement in Customer Experience and Revenue/Customer https://personalandprofessionalexcellence.blogspot.com/2019/07/cx-life-cycle-management-for-continuous.html
• AI for early detection of Customer Experience Fatigue and effective extension of CX lifecycle https://personalandprofessionalexcellence.blogspot.com/2019/08/ai-for-early-detection-of-customer.html

 

Customer Experience Measurement – Stand Alone v/s Rate of Change

Customer has become king again and is in a position to demand much more beyond better pricing and service from sellers. Sellers are also obliging in multiple unique ways to differentiate themselves in the eyes of customer. Several experiments are being made and significant dollars are set aside for this purpose. The ultimate motive of this push is to improve revenue from existing streams as well as add new revenue streams for the future. The success of the initiatives is measured in terms of how much the needle has moved.

There are two steps in this process; first step is, to define how we would measure customer experience and second step is, how do we connect this CX measure to Revenue movement. This kind of rigor is relatively new to CX and multiple options are being tried by organizations to connect it to revenue. It is not perfected yet, however learning from each experiment is improving the clarity.

An organization will need to answer these three questions to bring in clarity in their CX program as well as measuring benefits from the same.

1. Should Customer experience be measured as stand alone value or it should be measured in terms of rate of change in the CX measure?
2. Should we measure using Direct Customer Feedback or through Indirect (derived) feedback?
3. Should we use past data or future (predicted) data?

I have analyzed first question in this blog and identified possible way forward for companies.

Stand Alone or Rate of Change:

There are a few popular metrics to measure CX today; prominent being NPS and CSAT. Companies have devised ways to capture the NPS / CSAT score at definite intervals and use the feedback from each survey to create next round of initiatives. Some of the companies have built the necessary rigor in to their processes and collect the measurement at regular frequency. However, they still face some challenges like,

• The score is influenced many times by specific performance just before the survey and does not represent the entire period between two surveys 
• The highest frequency of such survey is Quarterly, but Half yearly or yearly is preferred due to investment of time and efforts in executing one cycle for company and customer
• Chances of bias in selection of respondents. Detractors or customers who did not make a purchase are missed out depriving the comprehensive CX level.

These challenges create limitations in terms of how fast one can respond, how comprehensively one can understand the trend as well as how to measure the actual impact on revenue movement.

If we want to understand the customer experience, how it is getting impacted by a specific initiative as well as how it is impacting revenue with minimal delay, observation of Rate of Change in CX is the answer. It provides us with the direction of impact and extent of impact together, which is critical to take the next course of action. Knowledge about success or failure of the initiative helps organization to make a kill or stop the losses, so faster is better. If the trend of CX is positive and rate of change is increasing, the initiative is working and impact is increasing exponentially. If the rate of change is zero, initiative has no impact on CX and mostly will not have any impact on revenue. Declining rate of change signifies decline in impact and possible revenue reduction.

The model in the adjacent figure depicts the status and revenue impact of a CX initiative through out its lifecycle. Typically, a positive burst in terms of increasing CX is seen at the time of introduction of new initiative and the relative impact reduces as the initiative matures. Slowly the impact is nullified and then ventures into negative territory. Once we map our initiative to the quadrant, we can determine our next steps.

Success of this model depends on frequency of capturing CX measure. Faster the capture, better the results.

With the current metrics used i.e. NPS or CSAT, it is almost impossible to capture the customer feedback at higher frequency due to the nature and mechanism of executing such initiatives. However, with the success of experimentation with AI/ML, certain algorithm-based metrics could be created using the data on inputs and outputs available with the company. This metric value could be calculated on daily basis or segment basis or geo basis to see how it is moving to plot it in the right quadrant.

Ref :    

• 1CX Life cycle management for continuous improvement in Customer Experience and Revenue/Customer https://personalandprofessionalexcellence.blogspot.com/2019/07/cx-life-cycle-management-for-continuous.html
• AAI for early detection of Customer Experience Fatigue and effective extension of CX lifecycle https://personalandprofessionalexcellence.blogspot.com/2019/08/ai-for-early-detection-of-customer.html

 

Predictable Customer (Internal) Experience Improvement- CIO Perspective

In my earlier blog, Predictability in Customer Experience Improvement – A Perspective for Grocery Retail  Industry, 

https://personalandprofessionalexcellence.blogspot.com/2019/07/predictability-in-customer-experience.html?_sm_au_=iVV4Rtj4p0NLfDVr, 

We deliberated on how do we use the differentiated-needs-pyramid to understand the needs of different set of customers for a Grocery chain and use it to define the initiatives and create a predictable improvement in the customer experience.

In this blog, we are going to apply the same technique to understand the internal customers for an organization unit and how we can create predictable improvement in their experience through planned initiatives. I have picked IT department as an example, which serves business; enables them to perform their functions effectively and achieve desired business goals. Business team is customer for IT team and IT team strives to provide a superlative customer experience to the business teams through their actions and initiatives. CIO being leader of IT unit can use this differentiated-needs-pyramid to understand his/her customer better and start planning on various initiatives to move the experience to higher level. The customer in this case, “Business Team”, is not a single block with common needs across, but have multiple segments with each one having unique needs as well as expectations from IT department. Combination of how CIO and team satisfies them and reinforces specific level again and again through multiple actions across these segments determines the experience perceived by customers. In this blog, I have considered two segments within the business team i.e. “Business Leaders” and “Business End users” to give further clarity.

The differentiated needs pyramid which has five levels starting from physiological needs to safety needs ultimately self-actualization, gets translated in to pyramid shown in the adjacent fig. The levels get translated as,  

1.     Availability of IT Support

2.  Comprehensive Coverage and Secure Landscape

3.   Business Feels that IT dept understands its needs well

4.    Business is proud of its IT

5.    Business Feels Nirvana

Each level is interpreted by different segments differently e.g. Business End users are predominantly concerned about the product / application they are using and if they are getting what they need from that application, they express greater satisfaction. Their experience does not change if the application used by some of their peers is not as effective/ useful giving them hard time. Whereas leaders would look at entire gamut of applications supporting their business and any one not servicing the needs will create a negative experience for them. Therefore, an action of fixing a problem in one application, could result into significant improvement of experience in a section of customers, no change for a section of customers and marginal change for another set of customers. Similarly Cost of IT is very important for leadership and not so for the Business End user community. Ease of use is more important to End user community than the leadership team, thus delivering a differentiated impact on customer experience after every action is taken.

Another aspect is interpretation of the level by segment. Let us take example of level 4, “Business is proud of IT”. For Leadership segment, it means they get recognized in their peer groups for using specific technology, products or something their IT team has enabled to do which has enhanced their business or made it more effective. The end user community will be proud of their IT if they get to work in the latest technology and opportunity to learn the latest and greatest in their area.

Following diagram shows the interpretation of the needs for two segments of the internal customers i.e. Business Leaders and Business End users for your reference

In real life, Business End user segment could be split in to some more like Finance End Users, End users on field (sales/Delivery/Service), End users in Manufacturing plant, etc. each group has a unique perspective on the IT support they need. Many more segments could be added.

There is a significant pull on every organization to go digital, implement IOT/AI/ML based solutions to address new business challenges. Let us take a situation where an organization wants to implement a customer facing application using Image recognition technology. It also decides to implement an automation solution in the warehouses so that it can create some funds which could be used for the new project. Let us examine the impact of these actions on customer experience for various segments 

1   Business Leadership – For this segment, IT is creating a futuristic solution for their business problem and has a potential to increase revenue. Coupled with it, IT is also working on another project which could bring in savings -- the action is hitting level 4 and 5 in positive way.

2     End User community in warehouse – This community has no connection with customer facing application and hence that intervention does not have any impact on their customer experience; Where as they are directly affected by the warehouse automation project and there is a possibility of negative impact due retrenchment possibility.

3   End User community in other departments like Finance, sales, etc. – No impact

Now, CIO can identify the impact on each customer segments he /she is servicing and map them together. The big picture would clearly signal if there are any proactive steps necessary to maintain the experience level as it is or is there a need to create another parallel initiative to maintain the experience at the same level in specific customer segment. This structured approach will help CIOs manage their customers well and maintain their experience in a continuous improving cycle.

Another way to use this approach is to map the experience levels of each customer segment at any time and then plan specific actions to improve specific customer experiences at specific levels for specific segments. Periodic mapping and measurement of customer experience for various segments will help identify right interventions, reduce wastage and create predictable improvement in Customer experience.

Ref : Customer Experience Improvement using Maslow’s theory   https://personalandprofessionalexcellence.blogspot.com/2018/03/customer-experience-improvement-using.html