Marketing - A Different Stance

The conventional approach of a Brand manager is to segment the market, target specific segments & position his or her product portfolio with a differentiation strategy. The brand’s performance will be measured by aggregate sales & profitability, while the incentives will be dependent solely on numbers. Companies which have been following the same notion are falling behind today.

In today’s world, almost all companies have the capability & infrastructure to interact with the customers directly, collecting & mining information about them & tailoring offerings according to their needs. With the advent of Data Sciences & SMAC technology along with concepts like Big Data, companies have the option of tracking down each customer & retain them for future. The 80:20 rule applies here as well; 80% of your revenue comes from 20% customers and those 20% customers are your repeat customers. To be sure, most companies use customer relationship management and other technologies to get a handle on customers, but no amount of technology can really improve the situation as long as companies are set up to market products rather than cultivate customers. There is a need for paradigm shift from mere transactions to maximization of Customer Lifetime Value (CLV); which implies bringing in the flexibility within the marketing department to create brands & products subservient for long-term relationships. The key distinction between a traditional and a customer-cultivating company is that one is organized to push products and brands whereas the other is designed to serve customers and customer segments. In the latter, communication is two-way and individualized, or at least tightly targeted at thinly sliced segments.

Nowadays, Mass marketing is effective only till a point. B2C marketing should take a leaf out of B2B marketing. The KRAs of Key Account Managers should be emulated in B2C as well. One of the best examples is IBM’s Insurance Process Acceleration Framework. Customer and industry specialists in IBM’s insurance practice work with lead customers to build fast and flexible processes in areas like claims, new business processing, and underwriting. Instead of focusing on short-term product sales, IBM measures the practice’s performance according to long-term customer metrics. In B2C front, Tesco has been an example of leveraging Data Analytics; from stocking items in their stores according to local tastes/preferences to Market-Basket analysis through complementary beer coupons for new fathers with every purchase of baby diapers. Data analytics with features like Customer profiling, Churn modelling, Customer segmentation analysis through Engagement scoring, Campaign response modelling, Customer Lifetime Value analysis & Perceptual mapping are paving the way for the companies to know their customers better & serve them accordingly.

There has to be a shift in strategy for companies today. The increasing opinions by consumers & customers flooding social media sites along with increasing call volume in customer care stations, points at a future where customer-cultivation will be the key to success. The involvement of customers into product creation is the future. In a customer-cultivating organization, Segment managers are encouraged to guide consumers for moving into a more-profitable brand from a less-profitable brand. The switching cost in this case might be high, but the emphasis is on Customer Lifetime Value than Sales. For example, P&G employs customer segment managers instead of product managers in major retail outlets like Walmart to guide customers in better buying.

In Pharmaceuticals, a lot of emphasis was laid on Customer Relationship Management in Sales front. Sales Representatives had their products & territories designated; so they liaised with Doctors on promoting a product. Traditional CRM tools have ruled the roost in the last decade. Hanks survey of 300 companies in North America: 42% of companies report that CRM is managed by the IT group, 31% by sales, and only 9% by marketing. Yet CRM is ultimately a tool for gauging customer needs and behaviors — the new customer department’s central role. It makes little sense for the very data required to execute a customer-cultivation strategy to be collected and analyzed outside the customer department. Bringing in CRM to the customer department means bringing in IT and analytic skills as well. But today, CRM has opened another front in the value chain. The concept of CRM being used for sales only has changed; now it caters to Patients as well. In “Patient Centricity”, Patients are the customers while Doctors & Hospitals are accounts through which patients can be routed indirectly. Patients are the end-users of medicine, yet their preferences & opinion never came into the limelight. “Patient Centricity”, the latest buzzword would establish a partnership among practitioners, patients, and their families (when appropriate) to ensure that decisions respect patients’ wants, needs and preferences and solicit patients’ input on the education and support they need to make decisions and participate in their own care. Patient involvement was never so high before, and neither the industry was so eager to interact with patients individually. As the business landscape of Life Sciences companies turn into digitization of their existing assets, “Patient Centricity” poses a new opportunity in customer involvement space. Patient centricity solutions need to interact with all key stakeholders i.e. Hospitals, Doctors, Patients, Third Party Risk Assessors, Healthcare Portals, Patient Community websites; which in turn presents great opportunities for Business Intelligence & cloud-based CRM systems. Here too, the need for Social Media analytics (through text mining & sentiment analysis), Knowledge portals, Customer Data Management and Segmentation rules are essential.

There is a new focus on Customer metrics nowadays. It’s a shift from product profitability to customer profitability; some products may be unprofitable to the company but strengthen customer relationships. Companies also need to concentrate on CLV rather than current sales. The customer lifetime value metric evaluates the future profits generated from a customer, properly discounted to reflect the time value of money. Lifetime value focuses the company on long-term health which in turn proves that customers retained incurring cost to the company in the initial stages, turn out to be profitable in the long run. Shifting their focus from brand equity (the value of a brand) to customer equity (the sum of the lifetime values of their customers) is essential in long-term. Companies need to pay less attention to current market share and more attention to customer equity share (the value of a company’s customer base divided by the total value of the customers in the market).

Conclusion:

Due to all of this & to enable companies function at their best today, there needs to be a change in the internal structures as well. A Chief Marketing Officer (CMO) usually holds the highest position in the Marketing arm & reports to the CEO. A position of Chief Customer Officer (CCO) needs to be created in parallel to CMO, who will work with the CMO in harmonizing strategies on customer segments & products. Customer managers will be most effective when they’re T-shaped, combining deep knowledge of particular customers or segments with broad knowledge of the firm and its products. These managers must also be sophisticated data interpreters, able to extract insights from the increasing amount of information about customers’ attitudes and activities.

Like any other organizational transformation, making a product-focused company fully customer-centric will be difficult; the transition is difficult irrespective of the quality of Change Management processes deployed. The IT group will want to hang on to CRM; R&D is going to fight hard to keep its relative autonomy; and most important, traditional marketing executives will battle for their jobs. Because the change requires overcoming entrenched interests, it won’t happen organically. Transformation must be driven from the top down. It is already the only competitive way to serve customers.

Patient Centricity

“Patient Centricity” is the latest buzzword in the Pharmaceutical industry & has the potential to disrupt the way the industry works commercially. It would establish a partnership among practitioners, patients, and their families (when appropriate) to ensure that decisions respect patients’ wants, needs and preferences and solicit patients’ input on the education and support they need to make decisions and participate in their own care. Patient involvement was never so high before, and neither the industry was so eager to interact with patients individually. As the business landscape of Life Sciences companies turn into digitization of their existing assets, “Patient Centricity” poses a new opportunity in customer involvement space.

Patient Centricity solutions need to interact with all key stakeholders i.e. Hospitals, Doctors, Patients, Third Party Risk Assessors, Healthcare Portals, Patient Community websites; which in turn presents great opportunities for Business Intelligence & cloud-based CRM systems. The need for Social Media analytics (through text mining & sentiment analysis), Knowledge portals, Customer Data Management and Segmentation rules are essential here. Fully-integrated solutions featuring business intelligence applications, data warehouse software, document processing, data normalization applications, Natural Language Processing (NLP) technologies, and search indexing/query software are ideal fits for Patient Centricity.

Features of Patient Centricity from Sales & Marketing perspective:

• Social Media/Patient Portals/Online Patient Groups
• Patient Education/Guidance/Awareness/Adherence Support (Knowledge Management)
• Patient & Physician Engagement/Digital Health Management (Patient Affiliation)
• Patient Profiling/Segmentation
• Treatment Monitoring via Remote Health Monitoring
• Personalized Medicine/Treatments/Medical Advice

Social Media/Patient Portals/Online Patient Groups

Pharmaceutical companies have started using social media aggressively to market much better and reach out to a wider audience. While complying with regulations, leading pharmaceutical firms are trying to connect with patients and spread awareness regarding diseases and health issues. Companies are also increasingly allowing patients to access medical information on portals that was previously available only to doctors. 

     Benefits to Patients

    

• Access to information is vastly improved
• Patients have a chance of improving their self-management of conditions and clinical outcomes
• Latent needs of patients can be understood
• Better connection with the larger patient community and forums

Measures for Social Media Engagement

•     IMS Health Reach Index - Reach is a measure of the absolute number of listeners and the index is based on the number of people reached by each channel through likes, shares and re-tweets.
•     IMS Health Relevance Index - Relevance measures whether people found posts or content relevant and/or useful, and the index is based on the extent to which content is being shared and forwarded across social networks. Relevance increases reach is an indicator that a social media platform is growing.
•      IMS Health Relationship Index - Relationship is a measure of interaction - the back and forth of conversation - and a measure of company and consumer or patient integration. The relationship index measures the level of interaction between a company and those who post, reply or otherwise interact with the company’s postings.

Patient Education/Guidance/Awareness/Adherence Support

Pharmaceutical companies have tried to move from a traditional role of a drug provider to a more advanced role of a health monitor. As part of this, they try and connect to patients through numerous online campaigns and implement initiatives that boost patient adherence to drugs and treatment plans.

Benefits to Patients

• Patients gain a more advanced understanding of diseases and can start managing their treatment process better
• Access to drugs, treatments and physicians improves
• With the necessary guidance and support, patients are more likely to adhere to dosage and thus lower chances of hospitalization

Patient & Physician Engagement/Digital Health Management

One of the best ways for Pharmaceutical companies to understand the needs of patients has been to work closely with patient networks. To improve their research and understanding of treatments, companies are also connecting with physician networks. Providing patients with increased access to physicians and information has been a priority for the industry.  

 Benefits to Patients & Physicians

• Transparency in working and a better understanding of patient needs
• Data on the patient social networks can be used to facilitate better research and drugs
• Easier access to physicians and treatments
• High quality clinical advice and consultations
• Understanding physicians’ unique clinical, professional and personal needs. Enabling them to better advertise their services and expand reach

Patient Profiling/Segmentation

Practice of regarding particular patients as more likely to have certain behaviours or illnesses based on their genome, age, appearance, race, gender, financial status, age, ethnic background, psychological traits, cultural mores or other observable characteristics.

   Benefits to Patients & Physicians

• Classification of patients into segments
• Identification of common needs within the classified Patient groups
• Addressing to the generic needs of the classified Patient groups

Treatment Monitoring

Treatment Monitor app provides a framework for medical professionals to track treatments prescribed and medical devices used by individual patients and groups of patients across a practice.

    Benefits to Patients & Physicians

• Provides a consolidated view of patients by device, treatment, or study group
• Tracks expiration dates of medical devices
• Enables reporting on effectiveness of treatment
• Treatment Monitor provides a way to manage medical records and track patient needs related to devices such as pacemakers and insulin pumps
• Easy to view related patient information and drill down on the outcome of treatment and the requirements for maintaining devices

Personalized Medicine/Treatments/Medical Advice

With the advancements in biotech and genome technology, companies have started leveraging this data to provide more personalized medicine and targeted therapies to patients. Pharmaceutical companies have realized that a single drug/treatment may not work similarly for all patients and have begun to understand the value of customer segmentation.  

    Benefits to patients

• Patients get a much more personalized treatment that takes into account their reaction and response to drugs/therapy
• Effectiveness of drugs can be improved significantly
• Access to fellow patients within similar subgroups/segments 
• More specific and targeted clinical advice and consultations

Pharmaceutical Industry - Integrating Sales with Manufacturing & Supply Chain

The global pharmaceutical industry is expected to be worth more than $1 trillion in 2015, marking a 5% compound annual growth rate. The market is highly competitive and entry is difficult due to a combination of strict regulations and the need for extensive research and development which entails huge upfront investment.

One of the major steps pharmaceutical companies need to take is to create better connectivity between different parts of their value chain. Much technological architecture is in the form of separate stand-alone systems – one for R&D, a quite different one for manufacturing & supply chain, and a completely different one for Sales & Marketing. This is becoming unsustainable with time as the companies continue to incur cost.

Technological and IT changes are critical if companies are to embrace the full potential of the FDA’s cGMP (US Food and Drug Administration’s current Good Manufacturing Practice) and new validation guidelines. They are equally critical to reduce drug development times. Technological innovation can radically reduce costs by minimizing waste. Investments such as quality by design (QbD), Process Analytical Technology (PAT), and product life cycle management and knowledge management tools are ways companies can prepare for live licensing while addressing the pressures of today. PAT in the plant delivers greater productivity at lower costs. QbD in R&D reduces process development, up-scaling and technology transfer time. Such investments can help companies deliver more flexible manufacturing, reduce costs, respond to regulations, and bridge the gap between R&D and manufacturing – and thus reduce the overall period of Drug Development Life Cycle (DDLC) and business risks. There should be a mechanism by which all medicines receiving approval will be approved on a real-time basis, with live licenses contingent on extensive in-life testing (including trials in patient sub populations). 

Pharmaceutical Value Chain:

In years to come, drugs are set to become more diverse and manufacturing technology more complex. Companies must focus on using product and process life cycle management systems. By introducing such systems, pharmaceutical companies can improve their responsiveness to new regulatory and official initiatives. These include the publication of the FDA process validation draft guidance, the International Society for Pharmaceutical Engineering (ISPE), PQLI (product quality life cycle implementation), live licensing submissions based on e-CTD (electronic Common Technical Document), and the ASTM E55 continuous quality verification standard. The Pharmaceutical Value Chain has to be leveraged by the integration of R&D, Manufacturing-Supply Chain with Sales-Marketing functions. The challenge for Pharmaceutical companies nowadays is fast transfer of information from R&D to Manufacturing on what is to be produced. The more you delay in manufacturing, the later you enter the market, the more you lose in competition & sales. Also, a mechanism is required which can link feedback from patients directly to the manufacturing process.

In Manufacturing, non-value added components within processes are identified and discarded to avoid costs. Good practices like Transfer pricing between units within the organization, outsourcing and leveraging third party logistic companies are critical in order to reduce costs. Highlighting SKUs for their respective Firm, Stand-off & Planning zones in demand planning enables better visibility between Manufacturing & Supply Chain. This article focuses on an integrated linkage between Manufacturing & Supply Chain with Sales, which is the most essential part in terms of revenue realization. We can logically divide the Pharmaceutical Supply Chain into two halves; one being “To-Market” & another being “In-Market”.

In-Market & To-Market:

“To-Market” includes the movement of goods from the Manufacturing site till the Wholesalers. It includes the local manufacturers and importers who make intermediate sales to the Wholesalers & Distributors. “In-Market” includes movement of goods from Wholesalers & Distributors to Retailers, Hospitals & Customers. A perfect scenario would be that the market demand is being fulfilled by the amount being produced. But the fluctuations in drug demand are generally high, especially with the entry of new players with competitor products. On an average, every drug has at least two competitors today. Because there is fluctuation, the usual industry practice is to revise forecasts every month for the future 18-24 months. So, the forecasting has to be done at the Product SKU level to achieve an accurate estimate of production and sales. There has to be a mechanism through effective metrics which enables end to end view from a pharmacy level to the production site with performance, trends and potential risks on the demand side. This will optimize the whole enterprise by providing real-time metrics linking country operations, regional and global functions. Due to the lack of early indicators in the planning process, it leads to discrepancies between In-market demand, financial forecast, real demand and To-market replenishment.

Therefore, it is difficult to understand inventory gaps and real demand leading to potential overstocks or/and underestimated demand. Commonly incurred costs are due to overstocks which lead to inventory costs along with threat of expiration of drugs; add warehouse space/rent to that. Producing below market demand leads to opportunity cost on market penetration & sales. These indicators in form of metrics need to be put in place so as to enable top-management in making informed decisions, thereby assisting in improving the evaluation of the opportunities as well as the risks beforehand.

Proposed Metrics:

All the metrics involved with Manufacturing & Supply Chain should be represented in units as well as value. Each Product and its SKU has its own price & production plan. For that to happen, a catalog of all SKUs with their individual units and unit prices has to be captured and maintained for each month.

The proposed To-Market KPIs are the following:

• To-Market Forecast
• To-Market Replenishment (Ordered Stock, Actual Stock, Replenishment Forecast & Actuals)
• YTD To-Market Sales (Actuals Vs Target)
• Month of Coverage (Stock Vs Forecast)
• To-Market Order Bias (Orders Vs Forecast)
• To-Market Order Fill Rate (Actual Sales Vs Orders)
• To-Market Financial Plan Variance
• To-Market Demand Plan Variance
• Demand Plan Vs Financial Plan (Variance)
• To-Market Absolute Error (Orders Vs Forecast)

The proposed In-Market KPIs are the following:

• In-Market Forecast, Target & Actuals
• YTD In-Market Sales (Actuals Vs Target)
• Month of Coverage (Stock Vs Forecast)
• In-Market Bias (Actuals Vs Forecast)
• Absolute Error (Inventory vs Demand)
• Actual Sales Vs Financial Plan (Variance)
• In-Market SKU (Stock-out, Below Target, On Target & Above Target)
• In-Market Sales Year Projection
• In-Transit Stock
• Inventory Vs Expiry

Bias calculation in Pharmaceutical Supply Chain can be two-fold; by calculating variance between two data elements on the basis of one month or on the basis of 3 months rolling (the 3 most recent months backwards including the current month). This is done to minimize fluctuations in demand forecasts and actuals. In most cases, forecast value of a particular month is referenced from lag-2 forecast version. e.g. Dec 2014 forecast value is referenced from Oct 2014 version of forecast (usually forecast versions have forecast values for a minimum of 12 months forward).

Considering an ideal case where Cost to the company is low & Effectiveness is high (as shown in the first quadrant), which translates into optimum replenishment. The point of “Optimum Replenishment” is achieved when there is minimal variance between Market demand & Production levels as per forecasts. Low Market Bias is achieved when there is minimal variance between forecasts and orders placed in actual. Subsequently, “Optimum Replenishment” & “Low Market Bias” across Manufacturing & Supply Chain results into Low Demand Plan & Financial Plan variance. Low effectiveness & low cost still translates to higher levels of replenishment required in comparison to optimum levels of replenishment. Replenishment is directly driven by efficiency & effectiveness & Market-Bias is directly related with Cost incurred to the company.

Defining KPIs:

Metric Name	Purpose	Responsibility for Data Collection	Frequency of Data Collection	Operational Definition	Data Elements
To-Market Forecast, To-Market Orders, In-Market Sales, In-Market Forecast	To find how much to produce for a particular month for each product	Operations	Monthly	A consolidated view (preferably bar chart) of In-Market & To-Market Forecast, To-Market Orders & In-Market Actuals. Forecasting for production is done keeping in mind the seasonality for certain drugs. Whereas for other drugs like specialty drugs forecasting is done on the basis of demand only. Various forecasting methods like Trend analysis, Moving averages & exponential smoothing are implemented based on the type of drug.	Previous month's To-market forecast & actuals.
To-Market Replenishment	To find how much to replenish distributor stocks for a particular month for each product	Operations	Monthly	The number of units to be added to the Wholesaler/Distributor inventory, in order to fulfill market demand. Usually, a pre-defined quantity (the stocks can last in days) is kept as a baseline in country level, known as Safety stock. The aim is to replenish at least up to the Safety stock limit for each of the SKUs. This calculation is based on the actual stocks of the past month & the forecasted sales of the current month. The reason being that the actuals on stocks can only be reported after the month ends & the forecasting gets revised based on the same.	Ordered Stock, Actual Stock, Replenishment Forecast & Actuals & lead time to replenish
To-Market Order Bias	To minimize the variance between To-Market Orders and To-Market Forecast of units to be manufactured	Sales & Operations	Monthly	Comparison between To-Market Orders and To-Market forecast of units to be manufactured. Statistically, it is the percentage lead of Orders over forecasted production. It should be calculated on a rolling basis for a minimum of 3 months. The calculation brings in moving average of Financial plans on quarterly basis to level out the fluctuations.	To-Market Orders & To-Market forecast for a period of 12 months.
To-Market Order Fill Rate	To tune the actual production levels in order to minimize the variance between To-Market Orders and To-Market Sales	Sales & Operations	Monthly	Comparison between To-Market Sales and To-Market units manufactured (Sales). Statistically, it is the percentage lead of To-Market Sales over Orders. It should be calculated on a rolling basis for a minimum of 3 months. The calculation brings in moving average of Financial plans on quarterly basis to level out the fluctuations.	To-Market Orders & To-Market actuals for a period of 12 months.
To-Market Financial Plan Variance	To determine the variance in the financial plans on a YoY basis	Finance & Operations	Yearly	Comparison between the Financial Plan for the current 12 months forward and that of previous 12 months. Statistically, it is the percentage deviation of the Financial plan of previous 12 months over that of the current 12 months.	Financial Plan of current 12 months forward & Financial Plan of previous 12 months.
To-Market Demand Plan Variance	To determine the variance in the demand plans on a YoY basis	Operations	Yearly	Comparison between the Demand Plan for the current 12 months forward and that of previous 12 months. Statistically, it is the percentage deviation of the Demand plan of previous 12 months over that of the current 12 months.	Demand Plan of current 12 months forward & Demand Plan of previous 12 months.
Demand Plan Vs Financial Plan (Variance)	To determine the variance between Demand Plan & Financial Plan	Sales, Operations & Finance	Monthly	(YTD Sales actuals + Orders within firm period + Forecast outside firm period)/ Full Current Year FP	To-Market Sales, To-Market Orders & To-Market Forecast for a particular year
To-Market Absolute Error (Orders vs Forecast)	To determine the variance between Orders To Market Forecast	Sales & Operations	Monthly	Percentages lead of To-Market Orders over To-Market Forecast (Forecast value of the particular month is taken from lag 2 forecast version). It should be calculated on monthly basis in terms of units per SKU.	To-Market orders & To-Market forecast (up to the current month for the year)
In-Market Forecast, Target & Actuals	To find out how much to supply to retailers for each product for a particular month in a given year	Sales & Operations	Monthly	A consolidated view (preferably line chart) of Forecast, Target & Actuals. Forecasting for supply of drugs to the pharmacies is done keeping in mind the seasonality for certain drugs. Whereas for other drugs like specialty drugs forecasting is done on the basis of demand only. Various forecasting methods like Trend analysis, moving averages and exponential smoothing are implemented based on the type of drug. Target is set by the business for the whole year based on the actuals of the previous year.	Previous month's In-market Forecast, Target & Actuals
YTD In-Market Sales (Actuals Vs Target)	To calculate the variance between Actuals & Target till a particular month of a year	Sales & Operations	Monthly	Percentages lead of In-Market Actuals over Target till a particular month of a year.	In-Market actuals & In-Market Target (up to the current month for the year)
Month of Coverage (Stock vs Forecast)	To calculate "Stock in Hand" and compare the same with pre-defined Safety stock	Operations	Monthly	This metric calculates “Stock in Hand” for a particular month with all the variables i.e. In-Market Stock, To-Market Stock, In-Market forecast, To-Market forecast and Orders. This calculation is done by cumulative deduction of Stocks forecasted and Stocks available over a period of 3 months (industry standard).	In-Market Stock, To-Market Stock, In-Market forecast, To-Market forecast and Orders for the current 12 months.
In-Market Bias (Forecast vs Actual)	To determine the variance between actuals and forecast of In-Market sales for each product for a particular month in a given year	Sales & Operations	Monthly	Comparison between In-Market Actuals and In-Market Forecast in terms of Sales. Statistically, it is the percentage lead of In-Market Forecast over In-Market Actuals. It should be calculated on a rolling basis for a minimum of 3 months (Forecast value of the particular month is taken from lag 2 forecast version). The calculation brings in moving average of all variables on quarterly basis to level out the fluctuations.	In-Market actuals & In-Market forecast (up to the current month for the year)
In-Market Absolute Error (Inventory vs Demand)	To determine deviation between inventory & demand	Sales & Operations	Monthly	Percentages lead of In-Market Forecast (Forecast value of the particular month is taken from lag 2 forecast version) over In-Market Actuals. It should be calculated on monthly basis in terms of units per SKU.	In-Market actuals & In-Market forecast (up to the current month for the year)
Actual Sales Vs Financial Plan (Variance)	To determine variance between YTD Actual Sales & YTD Financial Plan	Sales, Operations & Finance	Monthly	Percentages lead of YTD Actual Sales over YTD Financial Plan	In-Market Sales & Financial Plan up to the current month for the year.
In-Market SKU (Stock-out, Below Target, On Target & Above Target)	To determine the critically affected SKU's for each distributor, SKUs which are below country target, as per country target and above country target	Operations	Monthly	Number of SKUs which are in stock-out situation with Wholesalers/Distributors, SKUs which are below country target, as per country target and above country target for a particular month. This metric is calculated in conjunction with In-Market replenishment. Usually, a pre-defined quantity (the stocks can last in days) is kept as a baseline in country level, known as Safety stock. The aim is to replenish at least up to the Safety stock limit for each of the SKUs. This calculation is based on the actual stocks of the past month & the forecasted sales of the current month. The reason being that the actuals on stocks can only be reported after the month ends & the forecasting gets revised based on the same.	In-Market SKU Threshold levels, In-Market Forecast, In-Market Actuals (up to the current month for the year).
In-Market Sales Year Projection	To determine the difference in the actual and planned sales for a particular year	Sales & Operations	Yearly	The difference between the cumulative value of In-Market Actual and Forecasted Sales with the current year’s Sales Plan.	Sales Plan, In-Market forecast & In-Market actuals for 12 months of the particular year
In-Transit Stock	To accurately determine the inventory levels and replenishment needed for each distributor	Operations	Monthly	The amount of stock which is on-route to get delivered, but not delivered yet. It is important to know the In-Transit stock amount in units and dollars, which is factored in as an important variable for Replenishment calculation.	In-Market actuals (stock) & Stock in Hand (up to the current month for the year)
Inventory Vs Expiry	To compare the total inventory level with expired inventory	Operations	Quarterly	Amount of expired stock per SKU which forms a part of the total inventory. This comparison helps in estimating the percentage of expired stock over total inventory on a quarterly basis.	Total Inventory & Expired Stock (up to the current quarter for the year)

Conclusion:

These are only some of the basic KPIs suggested for an effective integration of Manufacturing-Supply Chain with Sales-Marketing, as per Industry best practices. Many organizations are now creating a classification called “Exception Products” – Products or SKUs which are either greater or less than a Targeted value. For example, Product A gets classified as an “Exception Product” if it doesn’t meet the Targeted Safety Stock level of 90 days (industry standard), for a given month. In addition, a lot of innovative visualizations have come up lately in Supply Chain area, to represent data effectively to the top management for faster decision-making process.

Thus, a comprehensive set of metrics in form of dashboards & reports will integrate two major blocks within the Pharmaceutical value chain i.e. Manufacturing-Supply Chain & Sales-Marketing. Companies have the option of choosing more insightful metrics aligned with their business needs. This will be the answer to minimization of cost across the Pharmaceutical Supply Chain & responding to Market fluctuations faster by providing prompt feedback from the market to the Manufacturing unit, thus negating risk & loss of opportunity.