Analyzing the data
Value Management
Analyzing the data
Value Management

Value Management encompasses a range of analyses and technique to extract more value from the existing customer base, without operations disruptions. Additional revenues can often be earned in a variety of methods, acting on commercial and marketing levers. This includes the management of churn, of migrations (from one higher-priced tariff or product to a cheaper one), and of customer value.


In very competitive markets (as the mobile telecom industry in most countries) the focus is nowadays more in nurturing existing customer than in acquiring new ones. The main reason is that existing customers generate often more revenues (ARPU) that new ones, which benefit from newer less expensive tariffs. When a customer ask to leave your company (or to migrate to another tariff plan) , the trade-off is between letting them go or incentives them through discounts and rebates to stay in the current situation, or as a fall-back position to migrate to an intermediate tariff plan, so that the corresponding revenue dilution is mitigated.


The difficult part is in deciding to which customer to make such an offer, what products (often below-the-line) to devise to such objective, how much money to invest to make sure to have a positive return, and most important to make sure that all front-end channels have the right tool, policies and procedures in place to act upon. Therefore the agent has to have a mean to get real time info such as ARPU (not monthly fee!), churn risk propensity, suggested tariffs, ...


Finally, the incentive and commission schemes that determine the payout for each single agent or salesperson has to reflect the strategy: if we want value (and not just volume), these schemes have to incorporate the value component in an appropriate way, and the agent has to have the tools to understand what is the value behind a specific product for a specific customer, and how far he is from his target.


I have personally dealt with these issues in several occasions, and have experiences first-hand the complexity of creating and fine-tuning the right tools, changing the mindset of all people involved, uniform all channels' behaviours, and monitor the results to quantify the obtained benefits

Revenue recovery

In this category I include all the ways to recover revenues that have been earned but instead do not materialise. Three typical examples are bad debt, credit notes and discount.


While lots of people and processes are usually devoted to try to minimise bad debt (e.g.: customer vetting, credit scoring, ...), less is often done to minimise the impact of credit notes and discounts. These two items are often generated during a sales or renewal negotiation process, when the agents give discounts in order to capture the sale. It is amazing, however, to find out in a typical organisation how quickly the credit notes/discount issue can get out of control. In a recent work, I found out a huge number of "unlimited 100% discount" in place, without anybody in the organisation apparently knowing much about it!


There are of course lots of "normal", authorised discounts, but there usually are also many of them that have slipped through the rules and policies applicable to a specific product, and are ingeniously used by sales agent to secure customer (and improve their commissions), although eventually they negative impact is higher than the value generated.


A thorough analysis of credit notes and discounts require a significant effort and strong collaboration from the financial function, but when done correctly it will certainly allow to identify vast areas for improvement, achievable by just enforcing existing rules or slightly modifying the sales policies.