Analytical Engine

Interesting things are taking place in pharmaceutical industry, which I believe has the potential to change pricing landscape of high cost drugs.

In June’07, the National Institute for Health and Clinical Excellence (NICE) of UK decided that Johnson and Johnson’s multiple myeloma drug, the one year treatment of which stands at around USD 48,000 a year, can be defrayed for if the company is willing to refund the cost in case of not showing a pre-decided level of cure.

This move towards sharing the risk of treatment outcome did not go unnoticed. Providers are all the more willing to share the risk of no-outcome with the drugs manufacturers. Biogen Idec, maker of Avonex for Multiple sclerosis drug that costs around $18,000 a year has made a dynamic pricing agreement with UK’s NICE. Under the plan, 5.000 multiple sclerosis patients are being followed for 10 years to see the effect of the drugs in slowing the progression of the disease. The prices of the drugs will be adjusted based on improvement of performance. Merck-Serono has offered to refund the primary care cost if its drug Erbitux if the patient does not respond within 6 weeks.

Although Europe seems to be leader in this development, but US companies are definitely taking note. United Healthcare have made an agreement with Genomic Health with United paying for the $3,460 genetic test to determine whether a woman with early-stage breast cancer would benefit from chemotherapy. If tests don’t have the intended impact of lowering chemotherapy United Healthcare will negotiate a lower price for the tests.

Essentially this development adds a new dimension to the pharmaceutical pricing, i.e, risk. Before pricing a drug, the point of paramount interest to both manufacturer and providers is what drugs are the ideal candidates for outcome-based pricing? The high cost drugs which are new in the market or have relatively low success rate seem to be the ideal target from the developments so far. The principal risk that companies should take into account is financial risk, which in turn will depend upon probability of no- outcome and amount of dollar exposure. Apart from regular variables such as physician’s ability, patient’s specific variables etc. there may be exogenous factors such as pollutions level for certain treatment which will affect the probability of outcome.

There are several interesting questions already. Will the companies have different refund policies for different locations? Will there be selection criteria? How will regulatory environment affect the risk-sharing?

We are at an interesting corner here. I will wait and watch how the pricing territory shapes up in the near future.

One of the most common problems of retail sector is pricing a product. There are numerous similar products lying in the shelves that are at different life stages and have complex interrelationship with other products & customers. Providing an optimal price of an SKU in order to extract maximum customer surplus is a challenge in itself.

In our recent stint with a Europe based retail chain for electronics goods, we helped our client use analytics to better price cell-phone accessories. A lot of advanced sophisticated pricing models can be built and deployed; however, when efforts and incremental value of such models are weighed against the approach of using elasticity and bundling, the latter option seems to be an optimal choice to get some quick hits for the business. For the uninitiated, here is a quick review of elasticity and bundling:

— Price elasticity of demand: The measure of responsivenesses in the quantity demanded for a commodity as a result of change in price of the same commodity.
— Product bundling: A marketing strategy that involves offering several products for sale as one combined product

Price elasticity approach: We calculated the price elasticity, and accessories that are having extremely high or extremely low elasticity along with reasonable business impact (sales volume or margins or life-stage) are picked for analysis. With the help of gross margins, we came up with the best price change for such accessories. In order to evaluate the financial impact, we built a business case to find out the potential revenue impact of such price changes.

Product bundling approach: A basic market basket analysis can help find products customers like to buy together. However, bundle needs to be evaluated for elasticity as well as likelihood of success before taking it to the customer. In order to increase the sale of some of the underperforming accessories, such accessories can be strategically bundled with highly elastic products. Gross margin of the bundle can be used for driving the price of the bundle.

Both these methods fetch actionable recommendations which can be tested in a very short time-frame in a test environment. One of our recommendations led to an additional £100K revenue impact per week for selected SKUs. A similar approach can be used for other items to better understand the nature and the monetary potential of the products lying in a store.

(There is no dictionary definition of P2P process, but often P2P is defined as a generic term used to encompass the payment for goods and services: The basic process of raising a purchase order, receiving the goods and paying the invoice is often put under P2P process .)

In a recently finished engagement with a manufacturing major, we leveraged Diamond’s procurement analytics solution to help the client identify dollar leakages and potential saving opportunities across their P2P process. This engagement had all the challenges associated with a large manufacturing setup viz. inbound and outbound from plants located across various locations, multiple vendors supplying the same raw material, a complex distribution and lack of unified IT systems. The list below can give you a feel of some the issues we identified –
1) Price variation/anomalies:
a. Procurement organization paying different price for the same raw material within the same time frame across different vendors
b. Price changes for certain non-contract items being anomalously higher (even in an increased demand scenario, where the organization might have had a chance to negotiate better prices)
2) Contract Adherence:
a. Shippers invoicing higher than the negotiated rates in purchase orders
b. Vendors charging prices which are not consistent with contract-negotiated prices
3) Freight Charge Variations:a. Different freight charges being charged for the same kind of delivery across supplies
b. Freight charges being consistently higher than industry standards
c. Variation in the freight charges for equal shipments from the same vendor Payment
4) Payment & Order Schedule:a. Payments made significantly prior to the negotiated deadlines leading to loss of revenue
b. Sub optimal volume discounts because of fragmented orders

Organizations are investing a lot of money and effort in IT solutions, designing data warehouse(s), and data collection methodology. These efforts, though, aimed at streamlining decision making processes, continue to exist in silos and are not creating the desired impact for the business. To help our client tackle this challenge, some of the things we tried to focus on, as part of the engagement were –

• Master Data Management: Integrating different data sources (General Ledger, Purchase Orders, Invoice, Vendor information etc.) and incorporating process information to come up with the final form of an analysis data mart
• Basic Data Profiling: Performing basic data validation, enriching/ cleansing and classifying required data, instead of building highly complex spend analyzers around existing solutions; The essence of all analytics done by a team should be the business benefit that can be derived, and not intellectual gratification
• Variance Reports: Leveraging the analysis data mart to create variance reports that help identify the variation in price/freights for a certain procured material
• Dashboards/Segmentation of the invoices : Developing a segmentation tool that helps identify where the money is invested/spent; Having a sense of where the dollars are going always helps businesses prioritize their spend rightly
• Payment segmentation: Identifying anomalies between the POs and Invoices, and keeping track of vendor issues such as reject rate/ quality, etc. can help renegotiate contracts, create appropriate procurement and penalty mechanisms for ongoing cost reduction
As can be seen, a significant part of our approach was about getting the basics right, and instituting basic analytics processes in place. Before moving on to advanced statistical concepts/techniques, we demonstrated the value of analytics through simplified dashboard and analytics reports,and showcased a potential saving of multimillion dollar to the client

A recent article in the New York Times discusses the impact of price on the perceived effectiveness of drugs.  The article describes an experiment where two groups of patients receive a placebo drug that they are told is a pain reliever, but the groups are told different price points.  After taking the placebo and receiving electric shocks, more people (85%) who were told it cost $2.50 reported pain relief than those who were told it cost only $0.10 (61%).  While the placebo effect is well-documented, this experiment highlights an important application to business – that a product’s price can be an effective marketing lever that can directly impact its effectiveness and value.

This is not the first time that cues such as pricing and packaging have been applied to marketing.  We recently collaborated with Professor Ariely (also quoted in the article) to explore the impact of applying behavioral economics principles to online marketing strategies.  One of the concepts we discussed in the resulting paper, is “Framing,” and we explored how consumers evaluate their options on relative terms, and make purchase decisions based on the cues given to them.  In the paper, we highlight the example of a magazine publisher who was able to steer consumers toward a higher-cost option simply by presenting a lower-cost one.  Even though no one chose the lower-cost option, it was an effective cue in that it showed the relative value of the higher-cost one.  In the drug experiment, price was the cue, and the higher price led consumers to find it a more effective (and valuable) product.

In our market segmentation work, we have found that different consumer segments require different value propositions, and that marketing messages need to emphasize factors such as features or pricing to appeal to their target markets.  Many generic, store-brand products are actually the same as the name-brand products, but are packaged differently and sold at a lower price to appeal to a different consumer segment.  The drug experiment highlights the same concept – and 61% of the patients who thought it was a cheap drug still reported that the product was effective in relieving their pain.

In developing marketing strategies, it is important to carefully consider the market segments you are targeting, along with the value drivers for each.  Understanding these drivers allows you to apply behavioral economics principles to maximize ROI through optimal pricing and product framing for each segment.

Heinz recently reported a very successful year driven in large parts by its pricing strategy. Increasing prices and simultaneously gaining market share is the holy grail of Consumer Packaged Goods (CPG) companies. A 2005 report from GMA, Nielson and McKinsey identifies some of the salient points around sales, pricing activities of ‘winning’ companies (which they define as companies who not only increased its pricing compared to its category peers, but grew their segment dollar share at the same time)

Setting Price:

• Manage pricing regionally (and some at the market area, micro-market, or even store level) to reflect local variations in price sensitivity that arise due to differences in consumer preferences, competitive intensity and retailer dynamics.
• Use more price elasticity analysis to set the price and integrate consumer insights into pricing more aggressively
• Tailor brand-pack assortment to the needs of a particular region, channel or store format

Realizing the Pricing Increase:

• Use a profit-based rationale to secure price increases and also combine this tactic with a strong understanding of consumer preferences, shopping behavior, and price elasticity.
• Appoint a single head of pricing who collaborates with top leadership and critical functions on both the pricing strategy and its execution. An essential part of that person’s task is then translating the strategy into sales force guidelines that help avoid conflicts between profit and volume goals.

In short, the winning companies are using analytics to drive their pricing decisions and have gone beyond the simple volume based pricing strategies that is the norm in the industry. Profitability, consumer insight, channel management and price elasticity are all areas which require data analytics capabilities. The end of the ERP implementation cycle in the industry means that companies will start developing predictive analytics capabilities and try to use information and analytics as a sustainable competitive advantage.