Principles & Rules

Establishing 'Making it Happen' as a 'Formal & Predictable' Discipline

Principles and Rules Home Page

To filter your Principles & Rules listing for a specific section, please click the relevant hyperlink :

Execution Making-it-Happen - Discipline of Execution → 'Executable' Strategy → Enterprise Senses and Intelligence → 'Capabilities' management → Resilience & Flexibility → Focus & Money-Machine → 'Value' management → Human Capital → Leadership & Work-Discipline → Entrepreneurial Execution → Execution Scorecard → Execution Intensity →

Enterprise Intelligence - BI End-to-End → Data Quality → Data-Warehouse/Mart → Data Analysis/OLAP → Metadata Management →

Functional Management - Customer Management → Sales & Distribution →

Vendor- IT Tool Domain - Vendor-tool Evaluation → BI End User Tools → BI platform Tools → Data Management Tools →

Page : 1 2

Build your internal capabilities for BI modeling and analysis

When it comes to developing an 'organizational brain' around BI, one should build internal capability to become technology and vendor-independent, without giving away the benefits of these two enabling entities.

Pre-designed BI frame-work and Models (LDMs) is double-edged sword

Pre-configured BI frame-works claim to be plug-and-play BI set-up with respect to a given industry and function. If it works for you, it can be a blessing, but if it does not, it can be much more pain, compared to doing it from scratch.

Articulate better for better BI decisioning

BI initiatives provide unique situations on decisioning. It is difficult to make a business customer to decide on which information he will and which he will not. This asks for better and clearer articulation to the business to enable faster decisioning.

Single Point Ownership of a cross-functional KPI- How to make it happen?

Any KPI needs to have a single point of ownership. However, there are generally multiple stakeholders, who contribute to the success of a KPI. This tip provides the tricks to drive a single point ownership while ensuring a collective effort.

Fix Business Intelligence at functional level first, before making it enterprise-level

There are many reasons on why one should let the data marts and BI evolve at functional level, before making BI an integrated enterprise platform. A big-bang data warehouse house is an impossible task and letting BI evolve at functional level will establish a solid base. However, one needs to have a robust and central governance to ensure that this evolution is happening in a consistent manner.

Big-Bang Enterprise Data Warehouse is a pipe-dream

A big-bang enterprise data warehouse is infeasible. One needs to have a phased strategy. The data warehouse at enterprise level has great benefits, and should be the point of arrival. However, there will be many milestones to cover before reaching the POA.

Using Synonyms and Views

Synonyms and Views create a user friendly layer for user access and querying. They also enable to make underlying database changes with minimum impact on user access interface.

Follow 70-20-10 development plan

Development Plan is not Training plan. Training is one of the means to achieve a holistic development. Development plan has three constituents- Training, Self-learning and on-the-job development. A development plan should typically have 70-20-10 distribution in terms of effort across these three constituents, with maximum effort around on-the-job development.

Maximize the output first and then the potential

A leader has seemingly conflicting objectives of putting best man for the job and developing people by giving assignments where an employee has low skill. This tip provides the tricks for managing this perceived conflict.

People become the way you treat them

Expect more from the people (without setting them up for failure), and pamper their self-esteem and they will explore new limits of their potential.

Be Shareholder-driven, customer-focused and employee-sensitive

A satisfied shareholder, leads to a loyal customer leads to an engaged employee

Be straight and blunt, till you team gets used to it

A manager builds his trust capital in the long-term, if he maintains a straight-talking persona, even at the cost of being unpopular in the beginning. Over the time, people get used to this style and start respecting the same.

Give performance feedback closer to the observation

As a suggested rule, an effective feedback has a shelf life of 48 hours from the point of observation

Feedback is not synonymous with negative feedback

Feedback is considered synonymous with the bad news and conflict-soaked discussion between manager and his employee. In reality, feedback can be both positive and developmental. A manager needs to give both kind of feedbacks with same level of intensity and sincerity.

Don't be guided only by the business requirements for your Business Intelligence

Business requirements around your BI initiative will be one of many other inputs and considerations, which will drive your BI model, design and architecture. Business information requirements keep on changing and by the time you deliver your Data Warehouse, chances are than a fair proportion of the information requirements might have changed.

For Core BI platform go for a single, established and robust player

Core Business Intelligence Platform includes Data Warehouse Server, Metadata management tool, ETL tool and OLAP server. These are the foundation/plumbing/infrastructure elements of your business intelligence. We recommend for you to go for a single and financially robust vendor for as many of these elements as possible.

Some considerations for Infrastructure in Data Warehouse

Data Warehouse infrastructure estimation is complex, as it is difficult to judge the use the Data Warehouse might be put to. Here are some considerations, which can help you to better estimate.

A KPI should be easy to understand- but depends on the level

A KPI should be ideally easy to understand. However, simplicity may be risky at senior management level.

Define the interpretation and actions related to KPIs

It will be helpful to document on how you can interpret the performance levels for a KPI and also the kind of actions it can invoke. This will be like documenting the managerial expertise.

For important KPIs- Install first and Fix later- though cautiously

An important KPI, which will drive your strategic performance, may not have the perfect support system. The idea is to include it in your scorecard and let the nature takes its own course of fixing it.

Shifting the mind-set to leading Indicators- KPIs

Managing by leading indicators make organizations more pro-active. It needs a change in the mind-set to push them to their right-ful place in a scorecard.

Never design your Business performance management systems on base of a specific KPI

A specific KPI is a good management practice. However, as you design your infrastructure to deliver the information around that KPI, you have to design around the KPI-class to which this KPI belongs.

Data quality assurance and control guidelines are no-brainer. Publish one immediately and evolve thereafter.

Publish Data Quality Control Guidelines is one of the simplest and easiest tasks you can do to kick-start your Data Quality Agenda. You can evolve these guidelines over time.

Cascade your standards and guidelines to business partners and Vendors

In today's world, when organizations are focusing on their core competencies, the supply and sales chains have well-integrated distribution partners and suppliers. These partners are virtually part of your organization. In this spirit, it is important to cascade your data management standards to your business partners. This sharing has the advantage of achieving a better integration and engagement.

Data Management standards for data entities are not only for IT systems

Data Management Standards for data entities involve setting up the universal and enterprise-wide domains, data models and business rules for data entities. Some examples are- Customer entity, product entitiy etc..Though the terminologies may sound techie, most of these will be defined by business and also used for running business and processes.

Data Management Standards for Data Entities will be a mix of collaboration and top-down

Data Management Standards for data entities involve setting up the universal and enterprise-wide domains, data models and business rules for data entities. This may create a challenge for some key entities like customer, vendor, product etc...The objective for setting-up universal standards is a combination of collaboration and executive decision. Skewing on either extreme could lead to lack of ownership and delays.

Field Tips Series#1- Data Mapping and Assessment

This page provides the Tips on sequencing of DMA, setting realistic data quality expectations, offline vs. online and how to delibk DMA from a staging area of DW.

Keep Aggregates and Details data in different Fact tables

One needs to store data in most granular form in the data warehouse. However, in certain situation, you may need to supplement the same with summary data to enhance the performance for predictable queries. One should have the detailed and aggregate data stored in separate fact tables.

Empower and Support Front-line Employees to resolve Customer Issues

Empowering front-line employees save time and effort, builds greater maturity in frontline staff, and brings greater customer satisfaction. Empowering frontline staff is a question of management mind-set and needs to be supplemented with a support system.

Handle Each Time-stamp in the Fact Table as a separate dimension

Typically there are multiple dates associated with a fact table. Place each data as a separate dimension.

Enabling Metadata Generation for Unstructured Content

Unstructured content in an organization is typically the last phase of evolution of a metadata environment. Most of the unstructured content is linked to business metadata. You can use various tools for content management, collaboration management and business process management to enable automatic generation of Metadata. There are some more basic methods like using shared drives and encouraging standard templates.

A smart manager is not the one who follows-up diligently

One can take the team productivity to next level by building a culture of 'no follow-up'. This saves everyone's time and also build greater leadership depth, accountability and empowerment.

Performance Review Session is last place to know the action-status

One need not wait for performance review session to know the status of key actions, which were agreed in the last review. A pro-active sharing of status will drive better execution and save crucial time of the review session.

New Data Standards- What about existing data and applications?

As an organization develops enterprise level data standards, it has to figure out the approach and plan for existing data and applications. One cannot have a big-bang conversion approach. Data Steward needs to drive a road-map, which focuses on the business case driven priorities, and also does a piggy-back on the mega IT initiatives.

Business owned applications are a reality- Manage it

Business owned applications seem like an inevitable reality, where businesses are funding, developing and managing the applications on their own. This leads to data quality issues and chaos. Instead of fight or flight approach, a CIO can embrace this reality and manage it to minimize risk and disruption. Added benefit will be a reduction in these non IT-owned applications over time.

Decision Management Process- An enabler to a Science and an Art

A flexible, adaptive, systematic, and result oriented decision making process can make your decision making more efficient, consistent and responsive.

How to integrate stand-alone BI environments- Gradual Approach

We recommend to go for phased approach for BI environment integration against a big-bang method. The reasons are lack of business and IT stamina, testing our assumptions, maintain stability and to develop our expertise. The phased approach should first go for integrating the plumbing work like ETL, followed by more front-end integration.

Which Metadata Architecture to use and when

Organizations have failed in the past to have integrated physical metadata repository, due to the reasons of technology diversity, lack of standards and sheer lack of stamina. As independent and multiple metadata repositories get developed, the more realistic solution is to have integration of these repositories while allowing them to function independently.

Aligning your rewards to your strategy- Aggressive Methods

While organizations change their strategy and strategic priorities, one needs to align the incentive and rewards more aggressively. Special pools for stratgic initiatives,higher reward pools for strategic roles and team incentives can help.

Master Data Management- Making a Right Start

Here is one brief de-mystifying and context-setting field-tip for master data management, which talks about the mind-set with which we should approach MDM. MDM is 75% definition+discipline and 25% MDM platforms and automation.

How to Maximize the effectiveness of Data Stewardship

Data Steward is a role with criticality and significant potential, if made accountable, empowered and positioned appropriatly in business.

Field Tips Series- Streamlining & reducing cost of Business Intelligence- Evaluate Open Source

You can reduce your costs, by gradually testing and adopting Open-Source BI in a select set of areas. Open-source BI is gradually gaining attention. Open Source BI is essentially business intelligence software which is open-source. There is a difference within open source and commercial open source. In this page we are talking about commercial open source (don't even think of pure open source, if you are a medium level enterprise and above), which is not free of cost but of minimal cost, with adequate support and services infrastructure. Pentaho and Jasper are examples of commercial open source.

Field Tips Series- Streamlining & Cost-Reduction in Business Intelligence- Governance & Standards

Governance & Standards essentially points to the consistency and robustness of managing change in the BI environment. The key issue behind high cost of BI is varied IT platform, standards and processed, which have additional over-head and also make BI inefficient & defective. As an organization we can undergo different types of changes, which have to dealt by effectve governance and standards.

Field Tips Series- Streamlining & Cost-Reduction in Business Intelligence- Licensing & Maintenance Contracts

Most of the large organizations have multiple contracts and licensing regimes for same platforms. For example, you may find multiple licenses for business objects in different markets for the same company.

Field Tips Series- Streamlining & Cost-Reduction in Business Intelligence- Consolidate Data-Marts

Every organization has organically and chaotically evolved on Business Intelligence. This has led to plethora of IT platforms and business applications, with cost and inefficiency over-head. This page shares the issue of Data-Marts proliferation, solutions and practical scenario in implementation.

Periodic Rationalization & Prioritization of Information has multiple benefits

Periodic Rationalization & Prioritization of Information has multiple benefits. This leads to information clutter and inefficiencies. A periodic clean-up will help, while you implement longer and more fundamental solution to this problem.

Beware of Data Federation as an ultimate solution to your data integration solution

Data Federation is essentially an ability to pick the data from various source systems and directly feed it into your OLAP and End-User tools. It means that one does not have to go through the painful process of Extraction, Transformation and Loading. Data federation also provides a "virtual" data-warehouse, where it can run a query across multiple systems as if it was coming from a singular source. However, it does not make Data Federation as your core integration solution.

Manage your Leads Database Centrally

The sales leads get generated all over the place in an organization. They get generated through a focused effort (like advertisements, events etc.) or at the level of each sales person, who has his own sales leads. It's a challenge to have the leads to be stored and tracked centrally so that an organization can have an understanding of how well the leads are being leveraged to boost sales.

Ask for dates instead of number of years

When you are doing any kind of data acquisition, (for example- generating a lead from a prospect, admitting a patient through an admission form, getting a customer to fill-up application form for your product), always try to ask for dates instead of tenure.

How to get more data along with Sales leads

Typically the amount of data you want get on a lead is inversely proportional to the number of leads you can generate. A potential customer does not like to fill-up long forms, even if you give incentives.

Page : 1 2