Linkdump – Web 2.0 and CRM

April 9, 2008 at 06:56 | In CRM 2.0, Oracle, Technology, VRM, Web, Web 2.0 | Leave a Comment

Using Web 2.0 to engage the customer - ThinkCustomers:The1to1 Blog

Bungee labs mashing up old-school crm with new-school Web 2.0 – CNET

On CRM Vendor Selection and Requirements Analysis

March 2, 2008 at 21:33 | In CRM, Technology, Vendor Selection | Leave a Comment

Richard Boardman, of Mareeba CRM Consulting has posted an article on CRM Requirements analysis and how this can help control costs when a company lays down clear requirements, before starting vendor selection for a new CRM system.

I agree with Richard that laying down a clear set of requirements is certainly necessary before selecting a CRM vendor and that some companies overlook their actual needs and the functionality of the selected product, which sometimes leads to challenges when undertaking the actual implementation of a CRM system.

I do feel however that one does not necessarily need to create a full blueprint of the CRM processes merely for vendor selection purposes. A high level specification, together with knowledgable evaluators of vendor’s propositions or products should also go a long way. The full blueprint can than be created, taken the functionality of the selected CRM package into account and ensuring that the COTS functionality purchased is leveraged in the right way.

On Vendor Relationship Management (VRM)

February 20, 2008 at 09:09 | In CRM 2.0, Social Networking, Technology, VRM, Value Proposition, Web, Wiki | Leave a Comment

Over the last week I’ve been diving into the concept of Vendor Relationship Management, which is being developed by CRM experts around the world and lead by a Harvard project group. Vendor relationship management is being defined as reciprocal to CRM. Vendor Relationship Management places the consumer in control of the relationship it has with several companies that sell the consumer certain products or services. The key is to not confuse this concept with Partner or Supplier Relationship Management which has existed for some quite some time in the Business 2 Business arena. VRM is a CRM for you and me as consumers and is fueled by the innovations and rise of the use of Social Media and Social Networks.

The concept
The project VRM pages do not offer a readymade definition of VRM, as the concept is still being worked on. The goal of VRM is clearly stated however.

“The goal of VRM is to improve the relationship between Demand and Supply by
providing new and better ways for the former to relate to the latter. In a
larger sense, VRM immodestly intends to improve markets and their mechanisms by equipping customers to be independent leaders and not just captive followers in
their relationships with vendors and other parties on the supply side of the
marketplace.” (Source: http://projectvrm.org)

Another definition is offered by one of the individuals participating in Project VRM, Alec Muffet.

“Technical outline: the feeds-based VRM concept is for you to be able to manage,
manipulate and share information – e.g. hotels you have visited, flights you
have taken, wines you have enjoyed – using a pluggable web-based software
platform similar to WordPress or Movable Type; however unlike those tools
which deal with free-form blog posts, instead your data is be stored as
objects (encoded in pertinent open-standards formats) which are then
“shared” via secure, self-referential, closed and authenticated ATOM or RSS
feeds that can be read, aggregated or further processed by “subscribers”
whom you authorize via your “friends list”.
The effect is: your data is held in one place and is authoritative.
Your subscribers can see it. When you change it, your subscribers will see the changes. No longer will you need to tell people when you change your address. They’ll already know.”(

Source: http://www.crypticide.com/dropsafe/article/2374)

Applications of VRM
VRM is an interesting concept because it is intended to make your live easier and provide you with more control over your relationship with vendors. It would be a great improvement if you would have a single environment where you can control the information you share with vendors and inform them of changes in your desires and contact details. In my view several solvable issues exist in further refining the concept of VRM and providing technology that can be used to manage your vendor relationships:

1. Trust, who do you allow to receive your information and updates? What kind of information are you willing to share with all kinds of vendors, and what information do you want to only provide to a small number of providers (such as bank and/or credit card details). I feel it would be necessary to define several trust levels and assign vendors a certain trust level (high, medium, low), that allows you to control who receives what kind of update, without the need to perform an elaborate setup of attributes for each vendor.

2. Technology providers, Alec Muffett mentions the re-use of existing technology such as MovableType and WordPress. Doc Searls, who is heading up Project VRM at Harvard also outlines the re-use of existing technology as one of the key points in further refining VRM. The issue I see here is that the technology selected must have a certain, and possibly very high, level of security, you do not want your updates to be readily available to wrong doers. I foresee an opportunity for companies that you already trust with your information and that provide a high level of security, such as PayPal or your Bank’s Internet banking application, to become key players in the VRM space.

3. Acceptance by vendors, user adoption is an issue with all kinds of applications and this also goes for VRM. Key Vendors, such as companies you interact with frequently (your cable company, cellphone provider, internet service provider etc.) should subscribe to your personal feed, if the concept is to become widely accepted. This means that your VRM feed needs to be based on widely accepted, open standards (XML / Web services), allowing companies to quickly adapt their systems to subscribe to your VRM system. Each platform that provides VRM functionality should also adhere to these open standards and not try to create lock-in by developing proprietary VRM feeds.

VRM Technology now
Within the Dutch Market there are already two interesting concepts that are VRM avant-la-lettre, such as the Rabo notabox (Dutch) and TNT Post’s Privver (Dutch) (Now de Digitale Brievenbus, or Digital Mailbox). Both services provide a way to digitally receive invoices, provide payments and send updates to a limited number of companies through a secure environment, in which you control which company you allow to send you a digital invoice.
When it comes to providing address and other updates to the outside world, Plaxo Pulse is perhaps one of the best examples of how a feed based system could work.

More information
A whitepaper was recently made available on Google Docs which provides more insight into VRM and possible applications. It would be interesting to see whether the VRM project is able to crowdsource a viable VRM solution with the help of industry experts around the world.

On Siebel UCM

February 2, 2008 at 12:27 | In CDI, CRM 2.0, Customer Data, Fusion, Oracle, Siebel, Technology, UCM | Leave a Comment

A couple of weeks a go I held an internal presentation on Oracle’s Siebel Universal Customer Master. I’ve been lucky enough to have been involved in two UCM implementations, for both version 7.5 and 8.0. I thought it wise to also share this presentation here. The presentation describes the product, advantages and drawbacks, as well as most likely implementation scenarios.

On CRM and User Adoption (2)

January 9, 2008 at 21:42 | In CRM, InsideCRM, Investment, ROI, Sales Force Automation, Survey, Technology | Leave a Comment

A little while ago I posted about the difficulty in getting Sales Representatives to use CRM applications, as opposed to Service Reps. A recent survey in California, by the Sales Lead Management Association, shows some interesting results, as quoted in this Chris Bucholtz article on Inside CRM. Chris quotes the survey’s somewhat suprising results:

“83 percent of the respondents don’t track ROI on investments in lead generation. Just 5 percent tracked ROI on SFA. How do these companies know whether their systems are helping or if they’re just making busy work for consultants or IT people?”

One could arrive at a number of conclusions based on this survey, such as:

  1. SFA Solutions are implemented for the simple reason that everybody’s doing it.
  2. It’s still difficult to measure ROI for CRM implementations.

I believe the main reason for not tracking ROI on SFA investments is the latter. Most companies simply do not know how to measure return, because the benefits of an SFA application are not always tangible and realized immediately after implementation. A series of blog postings on ITToolbox contains observations with regard to measuring CRM ROI, and can provide interesting insights for those who are struggling with the issue of CRM ROI.

On customer data integration (4)

January 4, 2008 at 12:15 | In CDI, CRM, Customer Data, Series, Technology, Value Proposition | 2 Comments

This is post 4 of a 4 part series on the concept and application of Customer Data Integration (hereafter referred to as CDI). The first post dealt with the definition of a number of concepts that make up the field of CDI. The second post, dealt with applying these concepts and defining an overall CDI approach. The third post dealt with key success factors in implementing CDI. This, the fourth post, will highlight some of the application solutions that provide CDI specific solutions.

Types of CDI applications

Two distinct types of CDI applications exists:

1. Data Quality Tools, aimed at improving data quality by providing cleansing and deduplication functionality

2. Master Data Management Tools, aimed at providing a single repository of customer data, made available to other applications through SOA functionality

This post is primarily aimed at the data quality tools (see table below). I will post on Siebel UCM and other MDM tools next week, outside of this series.

Table 1. DQ / Customer MDM vendors

Vendor Solution Type
Informatica Informatica Data Quality DQ
Oracle Siebel UCM MDM
IBM Customer Information File MDM
SAS / Dataflux Data Quality Integration Solution DQ
IBM / Websphere Websphere Quality Stage DQ
Trillium Software TS Quality Series 7

TS Discovery 5

TS Enrichment Series 7

 DQ
Human Inference Human Inference DQ Suite DQ

Informatica

Comprehensive suite of Data Quality solutions, IDQ (based on acquired Similarity Systems functionality), can be used for both online and off line cleansing and deduplication, provides profiling and migration tools through Powercentre functionality

Key characteristics

  • Flexible, allows for creation and maintenance of specific DQ rules
  • Single repository, easily distributed, simplifies maintenance
  • Ease of integration with both Oracle and SAP products, due to open architecture / adherence to SOA standards

Drawbacks

  • Only a small subset of rules is provided standard, one must build the DQ rules, leveraging functionality provided by the tool
  • Does not provide standard cleansing functionality (address / zipcode checks, naming conventions etc.)

IBM / Websphere

IBM’s Websphere suite provides standardised data quality solutions, aimed at both packaged applications, as well as to be used within custom application development.

Key characteristics

  • Supports multi language data
  • Easily import and export meta data
  • Pre-built objects and tables to define and customize data quality processes
  • Easy integration within J2EE custom built applications

Drawbacks

  • Requires Websphere background and programming experience
  • Perhaps less obvious choice when the MDM solution is an SAP or Oracle based packaged solution.

SAS / Dataflux

Dataflux Data Quality provides a single repository with which one can both improve quality of data, profile data to identify areas for improvement and deduplicate existing data in customer data systems. Dataflux is a wholly owned subsidiary of SAS.

Key characteristics

  • A single repository, with flexibility to customize Data quality ruling
  • Provides international support
  • Seamless integration with SAP

Drawbacks

  • Although internationally oriented, limited presence, relevance outside of US
  • Unclear what integration is provided with Oracle based products

Trillium

Provides applications that are used to both improve data quality as well as ensure integration and migration of customer data across the enterprise

Key Characteristics

  • Best–of–class status for global name and address cleansing.

  • Extensive automation of data profiling.
  • SAP Partner, easy integration

Drawbacks

  • Limited use for non-customer data

Human Inference

Human Inference provides a comprehensive suite of DQ tools that focus on compliance (SOx, Basel II, Anti-Terrorism) and deduplication and standardisation of customer data. The products HI delivers provide a rich set of out of the box functionality that can easily be leveraged.

Key Characteristics

  • Best–of–class status for global name and address cleansing.

  • Anti-terrorism specific functionality for financial services industry

  • Comprehensive algorithm for semantic comparison of name and address data

  • Provides out of the box functionality, which lowers the time to implement the solution

Drawbacks

  • Limitations in flexibility

Vendor conclusion

Over the years that I’ve been active in implementing CRM applications I’ve been involved in two CDI implementations that involved CDI solutions, one based on Informatica, the other using Human Inference. Whilst Human Inference provided a comprehensive and easy to use solution for the financial services industry in particular, I’ve found that IDQ is the best solution for companies looking for a flexible solution in which they can implement their own standards for matching, cleansing and deduplication.

On customer data integration (3)

December 6, 2007 at 10:34 | In CDI, CRM, Customer Data, Series, Technology, Value Proposition | Leave a Comment

This is post 3 of a 4 part series on the concept and application of Customer Data Integration (hereafter referred to as CDI). The first post dealt with the definition of a number of concepts that make up the field of CDI. The second post, dealt with applying these concepts and defining an overall CDI approach. This, the third post will deal with key success factors in implementing CDI. The fourth post will highlight some of the application solutions that provide CDI specific solutions.

Key success factors

Projects often fail, because the goals and targets are not clearly defined at the outset of a project. The key success factors detailed in this post are mainly derived out of this principle, and measuring whether your CDI implementation is still on target to achieve it’s goals. There are of course other KSF’s that one could list, but I’ve limited myself to the three below:

KSF 1. Get the basics right, define a data model first.

In implementing a customer master data application one has to define a uniform customer model (sometimes combined with a uniform product model). The uniform customer model should contain the definition of the attributes a customer has within your organization and which attributes are available in which of your domains. In other words, a customer for your organization is: Someone with a first and last name, a date of birth, social security number, a number of hobbies and a visiting and billing address. The address entity is made up of street, house number, zip code, city, country code etc. The hobbies may be interesting for your marketing department, but not so much for the billing department and as such is not a shared attribute. Define your a bandwidth for deviation in domains and agree on using this as the basis for application implementations. Be sure to leverage the customer master application you have selected, it usually has a standard data model that only need limited revision. Introducing a governance structure such as a design authority that monitors whether projects and departments stick to this guideline can help ensuring success. Only start implementing applications, once you have the customer model defined!

KSF 2. Consolidating customer facing processes

Look at all your customer facing processes, can they be consolidated or reorganized? Would it be beneficial to your organization to consolidate the existing customer call center into a single one, without the need for a customer master system? One of the main reasons behind needing a customer master systems is the need for consistent and on time customer data across channels and processes. If the processes and organizational elements can be consolidated, the need for a customer master system may diminish as well. In other words: get your organization in order, before trying to implement new technology!

KSF 2. One step at a time

The biggest benefits of CDI are reaped once every process is connected to the system of record for your customers, but this does not mean one needs to take one big jump straight to the top of the CDI mountain. This leap could either see you crash landing into the side of the mountain, or jumping over it and completely missing the goal. As with any IT implementation, try to break your CDI initiative into small steps, which deliver quick results while keeping your organization on the right road to climbing the top. Trying to reach the top with a turbocharged initiative could lead to you loosing out on business and not being able to work, once the turbo fails. Get your customer data model in order, get your processes aligned, try out your CDI system for a small department before slowly rolling out across your organization.

KPI’s

Success is not success if it’s not measured. In order to ensure one delivers added value through CDI one needs to measure whether improvements are made. In the second post I referred to identifying the pain as one of the first steps in implementing a CDI solution. This first step should also help you in creating a baseline measurement for your CDI KPI’s. The first KPI’s fall under the category data quality KPI’s:

  • Level of duplication (how many customers have you stored more than once).
  • Standardization of data (How many different ways do you to have to store a D.o.B. for instance?).
  • Data completeness (What percentage of attributes in your uniform data model has been given a value, on average).

Initial scores for the KPI’s mentioned in the bullets above can be found using data profiling tools (such as Informatica Data Quality ). Frequent measurement throughout your CDI initiative should allow you to measure whether your customer data improves over time.

  • Throughput time and measuring reduction. Is the time it takes to complete your customer intake or order intake process reduced? Is your customer information available across processes and channels quicker? Measure up front and measure during project execution to see a reduction.
  • Customer satisfaction surveys. An obvious KPI is to measure customer satisfaction and measure improvements over time. Are you customers more satisfied because they are able to quickly execute and close interactions (instead having to cal 3 times for each product a customer has, a move is handled with a single call).
  • Net promoter score. The amount of customers that recommend you or your products to others minus the amount of customers that discourage / recommend against buying your products to others. Also a key indicator of customer satisfaction. Does the NPS improve as your CDI initiative moves forward?
  • Number of complaints registered. Related to customer satisfaction, are your customers complaining less as your CDI initiative moves forward?

Post 4 – Vendor specific solutions

The fourth post in the series, which is to be posted next week, will dive into a number of vendor specific CDI solutions and their maturity.

On CRM in 2008

December 6, 2007 at 09:32 | In CRM, CRM 2.0, On Demand, Outsourcing, SaaS, SalesForce.com, Technology, Wiki | Leave a Comment

It’s time to look back at 2007 and gaze in to what the future holds for all of us. CRM Magazine features an article on CRM 2.0 and possible developments in the CRM arena in 2008. Interesting to see Mitchel Lager’s view of the future combined with the views and vision of several industry experts and research analysts. The focus of the article, as in CRM 2.0, is on collaboration, the collaborative enterpise and working together with your customers. Let’s see whether the trends and predictions in this article will indeed manifest themselves in 2008.

On the cost of customer data security

November 30, 2007 at 12:37 | In CDI, CRM, CRM Daily, Customer Data, Technology | Leave a Comment

Within the US security breaches for companies are leading to significant costs in order to re-imburse clients for privacy loss, improving security for IT applications and adapting to ever evolving technology developments. Read this article to find out how much US companies are loosing. I wonder what the cost of data security and security breaches is in the European market place, with it’s stricter and beter regulated privacy laws.

On Customer Data Integration (2)

November 29, 2007 at 12:51 | In CDI, CRM, Series, Technology, Value Proposition | Leave a Comment

This is post 2 of a 4 part series on the concept and application of Customer Data Integration (hereafter referred to as CDI). The first post dealt with the definition of a number of concepts that make up the field of CDI. This, the second post, deals with applying these concepts and defining an overall CDI approach. Post three will deal with key success factors in implementing CDI. The fourth post will highlight some of the application solutions that provide CDI specific solutions.

Defining a CDI Solution

There are many reasons for wanting or needing an integrated CDI environment, such as the need for a consistent customer view across all channels and specific touch points. One way of doing this could be to support all these channels and customer touch points with a single application and generic and uniform processes. Over the past years it has been proven to be rather costly and difficult to integrate legacy applications into a single platform, whereas this does not always lead to quantifiable benefits. A more feasible solution, especially in today’s Service Oriented Architecture World is to create a single system of record for customer data. This single system of record is then integrated to other applications over an Enterprise Service Bus for Create, Read, Update and Delete functionality (See slide 1 of the integrated Slide Share Presentation).

Climbing the CDI mountain

In order to reach the top of the mountain, or in other words an implemented CDI application, one would have to complete 4 distinct steps (see slide2 of the integrated slide share presentation). Much of these steps re-use elements of a typical CRM, Business Process Redesign or Generic Enterpise Application Implementation approach and may seem rather obvious.

  1. Identify the pain
  2. Develop the vision
  3. Select components
  4. Deliver value

each of these steps is detailed in the following paragraphs.

1. Identify the pain

If it ain’t broke, don’t fix it. First perform an assessment of whether a problem exists and if so, what the cause of this problem is. This can be either quality of data, such as customers that appear multiple times, with a slightly different spelling of the last name, or the fact that data or updates are not made available to all channels in a timely fashion. The pain-points are most easily identified through performing an customer data quality assessment and identifying all application, touchpoints and processes that use customer data. The outcome should be a simple identification of pain points and the rationale behind why they are pain points.

2. Develop the vision

The keyword in developing the vision is prioritization and value. Do not spend months of process re-engineering and application implementation work and budget on that one system that only makes up 10% of your customer contacts. Use the pareto principle and if simply developing a service bus that integrates two specific customer systems does the trick then do that, instead of trying to convert and integrate these two systems into a single instance. Focus on defining quick wins,for instance improve quality of data through applying a data quality tool such as Informatica IDQ or Human Inference on existing Customer systems, instead of developing new ones. Another example would be discovering that most value is gained by integrating two existing touchpoints, but not by replacing their systems. The outcome of this phase should be a roadmap and a business case.

3. Select components

Redesign your organization, technical application architecture and processes, based on the roadmap created in step 2. Select the tools for your CDI approach, what technology needs to be implemented and who is going to do it (a vendor, third party or someone / a department within the organization?). Also define who’s in charge of implementing the vision. The outcome should be a technology and organizational change focussed set of initiatives that are to be performed / completed within an 12 – 18 month horizon (preferably quicker)

4. Delvier value

Implement the initiatives and measure the result. Ensure your business case is met by identifying if the pain points have been resolved or partly resovled. Can you perform an administrative move of a customer quicker, do less customers complain that they still don’t have that product you promised and less customers complain on the quality of service and speed with which changes / complaints are handled.

The next post is on measuring how this value is delivered, what are do’s, don’ts and key performance indicators.

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