Profile data of migration leader

What skills do you need to become a data migration leader?

If you have gone through my posts on this subject, you will be able to guess!

1. Strategic thinker with excellent analytical skills, able to balance strategy with tactical execution
2. Excellent understanding of business process (flow of information, physical parts/products and finance) and
3. Excellent understanding of technology (Databases (SQL, Oracle), Business applications (ERP, PLM, CRM etc.), programming,
4. Project management whiz

This might be a tall order but start working on each of these skills. Practice makes perfect.

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"

Data Migration: A summary of my posts!

Over the last 3+ months, I have outlined my thoughts on data migration. In order to be successful with large scale implementations of business systems like (ERP, PLM, CRM, BPM etc.), data migration is a key element.

Data migration is often ignored and not enough attention is paid to this portion of the overall project.

The methodology I have outlined in these posts can be applied to a number of projects including data consolidation, server consolidation, migration from one application to another and the list goes on.

The key is to pay attention to the business needs and to make them successful by taking care of the technology and project management issues!

Good Luck.


1. Data Migration: Challenges & Joy!
http://improveprocess.blogspot.com/2009/07/data-migration-challenges-joy.html

2. Data Migration: Challenges & Joy!
http://improveprocess.blogspot.com/2009/07/data-migration-challenges-joy-part-2.html

3. Rules For Successful Data Migration
http://improveprocess.blogspot.com/2009/07/rules-for-successful-data-migration.html

4. Phases of Data migration
http://improveprocess.blogspot.com/2009/07/phases-of-data-migration.html

5. Phases of Data migration
http://improveprocess.blogspot.com/2009/07/phases-of-data-migration.html

6. Phases of Data migration: Analysis
http://improveprocess.blogspot.com/2009/07/phases-of-data-migration-analysis.html

7. Phases of Data migration: Design
http://improveprocess.blogspot.com/2009/07/phases-of-data-migration-design.html

8. Phases of Data migration: Test
http://improveprocess.blogspot.com/2009/08/phases-of-data-migration-test.html

9. Phases of Data migration: Validation
http://improveprocess.blogspot.com/2009/09/phases-of-data-migration-validation.html

10. Data migration: Risks
http://improveprocess.blogspot.com/2009/09/data-migration-risks.html

11. Tips for Successful Data Migration.
http://improveprocess.blogspot.com/2009/10/tips-for-successful-dat-migration.html

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"

Phases of Data migration: Validation

This is a key phase to ensure success of the overall migration effort! Validation sounds easy but how do you go about it?

I have always setup a 3 tiered validation criteria,

• First level validation is to ensure that the records from a count perspective made it in to the target system.
• Second level validation to ensure that the key data elements made it into the target systems. The key data elements I look for are data that are essential to the running of the business. Another condition I have used is select data that is part of the object’s properties and are required fields within the application layer. For e.g. part unit of measure, cost are part of the object’s key attributes in ERP/PLM systems,
• Third level validation is to ensure the metadata for attributes and keywords that are nice to have but don’t have a significant impact to the business if they were incorrectly loaded.

I approach validation from three perspectives with a focus on

• Ensuring proper extraction from source system
• Ensuring proper data transformation into flat files (CSV, XML etc.)
• Ensuring proper load into target system

If you analyze failures or errors, you have to start by reviewing what you extracted. If you have any doubts at this layer, then the success of the overall project will be in doubt. If the data is properly extracted but incorrectly populated into a flat file, then your load will not be successful. If you have been successful in extraction and transformation and have properly tested the loads then you should have the data loaded successfully into the target system.

One key issue always pops up when it comes to validation: WHO is responsible? In most cases, the business owners point to the IT guys and IT guys point to the business owners. In order to be successful, engage both teams and work through the development of validation criteria, success criteria and identify what can be automated, validate the automation routines so that both sides are satisfied.

Automating this activity is almost a must in most cases, when you are faced with gigabytes or even terabytes of data manual lookups will not be sufficient. You could get fancy and dabble with sampling theory. In my opinion, go for 100% checking by putting technology to work!

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"

Phases of Data migration: Test

Before any data is moved, it is important that some portion of the migration plan be tested and validated. Results of the migration test determine whether modification of the migration plan—for example, time line, migration tools used, amount of data migrated per session, and so on—is required. For example, if testing shows that allowable downtime would probably be exceeded, the migration methodology needs to be revisited.

Testing is a key element of the overall lifecycle of the project. Why? It

(1) proves the capability of migrating the data with no impact to the enterprise

(2) provides a good understanding of risks

(3) provides the ability to accurately define the sequence for the final migration including timelines

Start this process by reviewing the outputs from the analysis and planning stages. Engage a cross functional team and assess the capabilities, knowledge and expertise of the team. If the team has the skills, knowledge and expertise and has gone through a similar exercise in the past, then this phase is greatly simplified. Follow the same sequence as identified early.

In most cases, you might have to start from scratch. In that case, start by outlining the dependencies for data extraction, sequence them in the proper order, once the data is extracted from the source system, validate against the target system to ensure data integrity and then proceed with a sample load.

This is the time to engage your IT administrators to the fullest. Review application, database, network and infrastructure architecture and optimize from a data migration perspective.

For e.g. most data migration projects involve persistence in databases but this activity needs to be kicked off from the application layer following a syntax and methodology involving some structure in flat files (txt, xml etc.). In this case, the application and databases need to be tuned to identify the right parameters which will enable you to accomplish the load in a timely manner.

If you have distributed or federated systems, you will need the assistance of network and infrastructure administrators/architects to tune the network and servers from optimum performance, for e.g. remove bottleneck processes or establish a dedicated network etc.

This phase doesn’t conclude with successful migration and establishing a proper timeline for go-live. It should also include testing of post go-live activities. In most cases, search engines will need to be updated so that the indices are refreshed with the newly loaded data. there a number of such related activities that are tied to post go-live which are usually overlooked causing performance nightmares upon start up after data migration.

Keep at it, you can almost see the light at the end of the tunnel, next phase is validation. Remember the mantra “I love data”

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"

Cost Benefit Analysis

As part of problem solving approach, you will end up with multiple solution options, how would you evaluate each of these and pick the optimum solution?

Cost Benefit Analysis (CBA) is one of the evaluation techniques to identify the right solution; it is a widely used technique to analyze solution options and decide on an approach to remedy a problem or implement a solution for an opportunity. CBA provides a means for systematically comparing the value of outcomes with the value of resources required to achieve the outcome.

Generally feasibility studies analyze viability of projects and solutions; technical feasibility looks at factors like architecture and scalability primarily from a technical perspective. CBA focuses on economical feasibility and determines if a solution is cost effective and economically sound.

Best practices:

(1) CBA must document all assumptions

(2) CBA must contains at least 3 solution options, one of the options would be “no change” or “as is” condition, to highlight cost of avoidance.

(3) Customers /Stakeholder must be the ones to identify and determine how to measure and evaluate the benefits.

(4) Customers/Stakeholder must be interviewed to identify the potential impacts of new or modified systems.

(5) CBA must have data for 3-5 year time frame to paint a better picture of one time and ongoing costs and benefits.

Be mindful of the fact that both costs and benefits are made up of one time and ongoing elements.

Costs are made of the following elements:

Labor /Services- labor costs include the salaries and benefits of employees and contractors/consultants assigned to the project. Sometimes this may also be referred to as services costs.

Software – All applications or software which has to be purchased or programmed. This may include not only price of procurement but also cost of licenses over the maintenance time frame.

Hardware- Equipment required to implement solutions for e.g. CPU, storage, RAM, servers, laptops, desktops, workstations etc.

Training – costs related to training project team members, stakeholders, super users and the larger user community. This could include monies spent on training material, instructors, software, training delivery and workshops/conferences.

Depending upon the project type, you might need to look into additional cost items like materials, supplies, facilities, travel, lodging and telecommunications related costs. There might be projects or software implementations which would involve additional headcount requirements which may involve additional costs related to recruitment and so on.

A good place to start the documentation of costs would be the current setup Review activities and resources engaged in the current process this indicates the labor/service costs. Review current system architecture and identify all software applications, this will lead you to software costs, resources costs for administration and license/maintenance costs, hardware used and then to hardware’s cost, depreciation, maintenance.

Benefits are the services, capabilities, and qualities of each alternative system, and can be viewed as the return from an investment. To estimate benefits, first identify the benefits for both the customers and the organization that provides the service(s) to the customers. Start by analyzing a number of factors to thoroughly review all potential benefits like: Accuracy, Availability, Performance, Compatibility, Efficiency, Maintainability, Modularity, Reliability and Security. Some might refer to benefits as return on investment (ROI).

At a simplistic level, if you compare the costs and benefits of each of the solution options then you are doing cost benefit analysis. In later posts, I will discuss how this type of analysis can be combined with other techniques to evaluate all solution options for e.g. maturity of solutions, impact to business process, technical feasibility etc.

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"

Phases of Data migration: Analysis

This is probably the trickiest part of the project. It all depends upon how well you know your data!

In an earlier post, I had outlines the characteristics of good data. Focus on the following items in your analysis.

* Completeness,
* Conformity,
* Consistency,
* Accuracy,
* Duplicates, and
* Integrity

Based on your scope, try and identify all the sources of data (business systems like ERP, CRM, MES, PLM, document management systems etc.). Once you have the source identified, identify the quality of data.

If you have business analysts on your team, put them to work to

(1) document business rules and logic in source and target systems

(2) document gaps in data conformity to existing business rules and business processes

(3) document duplicates and plan of action to address duplicates

(4) document data integrity gaps and plan of action

(5) document plan to map data from source to target systems

Your business users should be assigned to

(1) assess completeness of data

(2) assess impact of data mapping

(3) assess data quality issued reported by business analysts

Based on the two bodies of work, you will have a good idea as to whether you need to clean your data prior to the move! In my experience, you will have some tough choices to make: Clean source data or design your extraction utilities to account for the cleansing actions!

I would recommend focusing on this aspect. “Garbage In is Garbage Out”

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"

Phases of Data migration: Planning

In an earlier post, I had outlined the key elements of a data migration plan. Now let us delve into the details.

(1) Scope: Clearly identify what data needs to be migrated over from the source system into the target system. Insights of subject matter experts are invaluable, Use them well! Work with your team, to identify what needs to be migrated, base the decision on how the business process will have to be executed in the new system and what information is essential to ensure success, effectiveness and efficiency. In every migration project I have managed, this is a crucial building block. At the end of this stage, you should have Estimate of the data assets (number of records, metadata, documents etc.)

(2) Criteria for a successful migration: this deliverable is closely tied to the scope of the data migration. Migrating the data into the target system without any errors doesn’t mean the project was successful; focus on what your customers will need! The criteria should start with error free migration and also include impact to customers if additional cycles are involved. This will take a few iterations, engage your subject matter experts and end users and work with them to refine the scope and define the criteria for success.

(3) Decision making authority of each of the data domains: In my experience, ownership of data is a tricky item. Different groups may own pieces of information that make up usable data to the enterprise! First identify the data elements and then start asking for who is the owner or steward of this data; this will lead you to decision making authority. Ensure that this person is always engaged, communicate often and well! Without their buy-in, scope and criteria for success will be meaningless.

(4) What data needs to be migrated: in almost all cases, all the data mayn’t be required. Consider the lifecycle of the information, in most cases the data can be divided into three buckets

a. Currently relevant to business

b. Historic information for archival / research purposes

c. Newly created, which may not have any significant value yet

Consider these buckets well, in most cases you might need to splice the data and truly identify all facets of usage. Dig deep and clearly identify usage patterns, this will indicate the value of your dataset and will provide insight into your final decision of partial or complete migration

(5) Timing: this is a key element of your plan. You need to clearly identify the time line for cutover into production. Work backwards from go-live date and identify spots for key tasks like development of extraction, loading and validation utilities, test runs (at least 2-3), stakeholder acceptance tests. You mayn’t have a clear idea of time needed to load into target system, work with your software vendor or benchmark with companies/individuals who have worked on similar systems and assess the time required for final migration.

(6) Requirements: focus on resource, system (hardware/software) and budgetary requirements. Gather as much information as possible from benchmarks and vendors to clearly identify what you might need to ensure success of this project. Start communicating the requirements to program sponsors, your resources and stakeholders, get alignment and then go secure the requirements.

(7) Roles and responsibilities: clearly define the roles and responsibilities for each and every one on your team. At a minimum, your team should include

a. Project manager or lead

b. Business user

c. Business analysts

d. Data architect and or data administrator

(8) Assumptions: this is a key element of any project, as you define the scope and success criteria, ensure that your assumptions are well documented and communicate them. Ensure your stakeholders, program sponsors and decision making authority are aligned. If you ever have to change any of the underlying assumption, secure alignment again.

(9) Risks and Risk Mitigation: every migration project is fraught with risk, if you remember an earlier post, I had outlined the success rate of projects and this paints a dismal picture. For every risk, ensure you have a risk mitigation plan. Document the risk and communicate your plans and secure alignment before proceeding.

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"

Phases of Data migration

Just like SDLC, I would like to propose distinct phases and stage gates that have to be met in order to complete data migration.

(1) Strategy

(2) Analysis

(3) Design (& build)

(4) Test

(5) Validation

In this post, let us focus on the strategy or planning phase. The first step is to put together a plan. The data migration plan should describe, in detail,

(1) Scope of the project

(2) Criteria for a successful migration

(3) Who is the decision making authority of each of the data domains (should be from the business organization)

(4) What data needs to be migrated (full or a subset)

(5) Timing

(6) Requirements from hardware, software perspective

(7) Resource requirements

(8) Budget requirements

(9) Roles and responsibilities

(10) Assumptions

(11) Risks

(12) Risk mitigation / Contingency

The plan also sets expectations up front with customers about the complexity of the migration, timing, and potential issues and concerns. Remember this is the first cut at the plan; this can be refined as move along your project. If you make any changes, remember to socialize with governance and accountability system.

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"

Rules For Successful Data Migration

(1) Clearly define the scope of the project

(2) Actively refine the scope of the project through targeted profiling and auditing

(3) Profile and audit all source data in scope before writing mapping specifications

(4) Define a realistic project budget and timeline, based on knowledge of data issues

(5) Secure sign off on each stage from a senior business representative

(6) Prioritize with a top down, target driven approach

(7) Aim to volume test all data in scope as early as possible at unit level

(8) Allow time for volume testing and resolving issues

(9) Segment the project into manageable, incremental chunks

(10) Keep total focus on the business objectives and cost/benefits throughout.

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"

Data Migration: Challenges & Joy! Part 2.

Forewarned is forearmed

Before we jump into details about migration methodologies, let us step back and understand some of challenges ahead of us. Whether you are migrating from a legacy system or a spreadsheet/database, you have to understand everything about your “SOURCE” system.

Common misconceptions about migration

• Data migration is an IT job function.
• We know our data!
• Data migration is one of the last steps taken before you go live with the new system.
• We can always change it after we go live.
• Acquiring legacy data is easy.
• Existing data will fit the new system.
• Existing data is of good quality.
• Existing data and business processes are understood.
• Documentation exists on data rules and formatting.
• We Don’t Need Tools or Special Skills
• Migration Is a Separate Activity

What you as the lead of the migration effort need to do is work with your team to dismiss these misconceptions.

Data migration is not a matter of copying data! In order to be successful at migrating data, one has to thoroughly understand
(1) Why is the data being migrated, significance and value to the organization?
(2) What data is being migrated?
(3) Where does the data reside currently?
(4) What are the rules for the data in the “Source” system and how is the target system setup?
(5) Who are the experts for each of the data domains?
(Hint: do not limit yourself to an IT resource)
(6) What is the success rate of migrating into this application?
(7) Who else in your industry segment has been through this activity?
(Hint: Do a benchmark)
(8) What do you need from a hardware/software perspective to support the data migration?
(Hint: Benchmarking and reference calls will provide this information)

Now that you armed with some answers which will highlight what you need to focus on, we can step back and think through our methodology.

Don't lose your humor, remember your mantra “I love data migration”

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"

Data Migration: Challenges & Joy!

What is data migration?

Data migration is the process of transferring data between storage types, formats, or computer systems.

Over the last decade, I have led multiple data migration efforts and found each one of these projects challenging and enriching. I keep swearing that I will not take up another but yet I always do. In a series of posts, I am going to share my experiences so that you may benefit from my lessons learnt and insights.

Common Data Migration Scenarios: when would you have a need to migrate data and create a project around this activity?
1. Mergers and acquisitions
2. Legacy system modernization
3. Enterprise application consolidation, implementation, or upgrade, such as an SAP ERP or CRM implementation
4. Master data management implementation
5. Business process outsourcing

Why are Data Migration Projects Are Risky: If you have been assigned as the lead for data migration, be aware of the heavy odds against you! Do your research and do it well.
Based on reference documents I have researched over the years (Gartner, Standish Group Study), I have found that
1. 84 percent of data migration projects fail to meet expectations
2. 37 percent experience budget overruns
3. 67 percent are not delivered on time

Why Data Migration Projects Fail: In earlier posts, I have outlined the importance of data management and the pitfalls of bad data management. These contribute to the overall success/failure of large implementation (and its data migration). Here are some reasons that have been attributed to failures of data migration.

1. Lack of methodology
2. Unrealistic scope
3. Improper understanding and use of tools
4. Inattention to data quality
5. Lack of experience

While data migration is essential to the success of implementation of a new application or business system, its role in the project often overlooked and underestimated. The common assumption is that tools exist to extract and move the data into the target application, or that data migration is something a consulting partner will handle. Often project teams tasked with data migration focus solely on the timely conversion and movement of data between systems. But data migration is not just about moving the data into the new application; it’s about making the data work once within the new application. This means that the data in the new application must be accurate and trustworthy for business users to readily transition from their legacy applications to adopt this new application.

In upcoming posts, I will outline the methodology I have used and why I have chosen this approach. Most of my team members would fondly remember my mantras of “Wash, Rinse & Repeat” and “I love data migration”. :)

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"

Knowledge management

I have long been a proponent of knowledge management – documenting insights, experiences and lessons learnt so that we don’t reinvent the wheel. In most cases, organizations and individuals tend to forget the lessons learnt in the past…

Over the last two decades or so, with the advent of enhanced document, content and metadata management solutions (ERP, PDM, PLM, Sharepoint, etc.) organizations have been able to document their best practices and lessons learnt to enable faster collaboration, innovation and problem solving.

There have been challenges such as the (1) need to classify and tag knowledge,(2) the need to clearly document experiences so that relative newcomers can come up to speed, (3) ability to search and find relevant data amongst thousands of documents (4) enforce creators and audiences of knowledge sharing to use the knowledge management system and positive value over time.

I was surprised to read an article on “When Knowledge Management Hurts” from http://blogs.harvardbusiness.org/vermeulen/2009/03/when-knowledge-management-hurt.html. An excerpt from this page “The advice to derive from this research? Shut down your expensive document databases; they tend to do more harm than good. They are a nuisance, impossible to navigate, and you can’t really store anything meaningful in them anyway, since real knowledge is quite impossible to put onto a piece of paper.”

I dug a little deeper and found “Does Knowledge Sharing Deliver on Its Promises?” from http://knowledge.wharton.upenn.edu/article.cfm?articleid=1841. This article clearly identified some of the shortcomings and listed some reasons why! The key takeaways from this article (my $0.02) are:
The first key implication is that it is unsafe to assume that more knowledge sharing is always better.
The second key implication is that it unsafe to assume that the net effects of using even the right type of knowledge are always positive. Instead, the design of a project team affects its ability to achieve the desired advantages of knowledge sharing.

As long as we continue to generate data, we should be able to leverage this! This will mean that users, employees and organizations will need to step back and understand the value in maintaining knowledge and experience within their boundaries and implement steps to capture, share and use knowledge effectively.

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"

The 10 Questions Every Change Agent Must Answer

I came across this blog entry, from Harvard Business School. I highly recommend reading the article and going through each and every one of the questions to see whether you are on the right track!
It's time to do — and get — something different. Here, then, are ten questions that leaders must ask of themselves and their organizations —
1. Do you see opportunities the competition doesn't see?
2. Do you have new ideas about where to look for new ideas?
3. Are you the most of anything?
4. If your company went out of business tomorrow, who would miss you and why?
5. Have you figured out how your organization's history can help to shape its future?
6. Can your customers live without you?
7. Do you treat different customers differently?
8. Are you getting the best contributions from the most people?
9. Are you consistent in your commitment to change?
10. Are you learning as fast as the world is changing?

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"

SWOT Strategy

In a previous blog entry, I had described how to go about SWOT analysis. Now that you have completed the analysis and created a matrix of your Strengths, Weakness, Opportunities and Threats, let us discuss how you can construct a strategy to address your findings.

You will have to match each component with one another. For example, match the internal strengths with external opportunities and list the resulting Strengths / Opportunities strategies in the matrix chart. This will result in four strategy types, which are:

S-O strategies pursue opportunities that match the company’s strengths. These are the best strategies to employ, but many firms are not in a position to do so. Companies will generally pursue one or several of the other three strategies first to be able to apply Strengths-Opportunities strategies.

W-O strategies overcome weaknesses to pursue opportunities. Your job is to match internal weaknesses with external opportunities and list the resulting Weaknesses-Opportunities strategies

S-T strategies identify ways that the firm can use its strengths to reduce its vulnerability to external threats. Your job is to match internal strengths with external threats and list the resulting Strengths-Threats Strategies

W-T strategies establish a defensive plan to prevent the firm’s weaknesses from making it susceptible to external threats. Your job is to match the internal weaknesses with external threats and record the resulting Weaknesses-Threats Strategies

Here are some examples on the type of strategies based on SWOT analysi:

Strength-Opportunity Strategies
Expand
Increase advertising
Develop new products
Diversify

Strength-Threat Strategies
Diversify
Acquire competitor
Expand
Re-engineer

Weakness-Opportunity Strategies
Joint venture
Acquire competitor
Expand

Weakness-Threat Strategies
Divest
Retrench
Restructure

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"

Quotes on Innovation & Leadership

I recently came across a few quotes which I found very inspiring and felt that these captured the essence of Innovation & Leadership.

Enjoy :)


The ability to convert ideas to things is the secret to outward success. (Henry Ward Beecher)

A wise man will make more opportunities than he finds. (Francis Bacon)

Six essentials for success: Sincerity, personal integrity, humility, courtesy, wisdom and charity. (Gerald Roque)

In everything that ends well defined are the secret of durable success. (Victor Cousins)

People seldom become famous for what they say until after they are famous for what they’ve done. (Cullen Hightower)

It is curious that physical courage should be so common in the world and moral courage so rare. (Mark Twain)

Things that matter most must never be at the mercy of things which matter least. (Goethe)

The significance of a man is not what he attains but in what he longs to attain. (Kahlil Gibran)

If you don’t know where you are going, you’ll end up somewhere else. (Yogi Berra)

People who are quick to take offense will never run short of supply. (Unknown source)

The greatest enemy of the truth is very often not the lie - deliberate, contrived and dishonest - but the myth - persistent, persuasive and unrealistic. (John F. Kennedy)

The greatest of all faults is to be conscious of none. (Thomas Carlyle)

The biggest idiot can sometimes ask the questions the smartest man can’t answer. (Unknown source)

Our plans miscarry because they have no aim. When a man does not know what harbor he is making for, no wind is the right wind. (Seneca)

In the absence of clearly defined goals, we become strangely loyal to performing daily acts of trivia. (Unknown source)

The woods are lovely
dark and deep.
But I have promises
to keep
And miles to go before
I sleep.
(Robert Frost)

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"

SWOT Analysis

SWOT Analysis is a methodology used to evaluate the Strengths, Weaknesses, Opportunities, and Threats involved in a project or in a business venture. It involves identifying the internal and external factors that are favorable and unfavorable to achieving success.

Successful businesses and individuals build on their strengths, correct their weaknesses and protect against internal vulnerabilities and external threats. They can monitor overall business environment and quickly identify and exploit new opportunities faster than competitors.

SWOT analysis can be used for all sorts of decision-making, and the SWOT template enables proactive thinking, rather than relying on habitual or instinctive reactions.

SW – Strengths & Weakness are influenced by internal factors – the strengths and weaknesses of the organization or individual. These are competences and resources that the organization or individual possesses and that are under their control.

OT - Opportunities & Threats are influenced by external factors that an organization or individual faces from trends and changes in their environment. These external factors are not under the control or influence of the organization or individual

How do I go about it?

(1) Start with an objective

(2) Now/Present: identify your strengths and weakness,

a. Strengths

i. What are your advantages?
ii. What do you do well?

b. Weaknesses

i. What could you improve?
ii. What do you do badly?
iii. What should you avoid?

(3) Future/What might be?: identify potential opportunities and threats

a. Opportunities

i. Where are the good opportunities in front of you?
ii. What are the interesting trends you are aware of?

b. Threats

i. What obstacles do you face?
ii. What is your competition doing?
iii. Is changing technology threatening your position?
iv. Could any of your weaknesses seriously threaten your potential?

(4) Develop a plan of action to

a. maximize strengths to turn them into opportunities,

b. maintain and leverage strengths

c. convert weakness into strengths, create a remedial action plan to improve

d. counter or minimize threats, if not threats will turn into weakness

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"

Marcel Proust on Discovery/Innovation

"The only real voyage of discovery consists not in seeking new landscapes but in having new eyes"

Do you see opportunities where others don't? Do you know where to look for new ideas?

On a personal note, I have found that this approach of "fresh eyes" is very useful!

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"

Leading Change. Part 1

First step in becoming a successful change leader is to fully understanding your organization and matching the initiative to your organization’s real needs. This means not just adopting the latest management fad or implementing solutions for the sake of implementing new and emerging technologies.

Recognize that bringing about useful and meaningful change is fundamentally about changing people’s behavior. It is not primarily about installing a new system or business process. If people in the end do not behave and work differently, then the money and time spent in “doing stuff” is wasted.

How do you go about becoming a change leader?

(1) Focus on needs of the business. Understand the business (environment, business processes, business strategy, business needs (current and long term). Don’t assume anything, especially when considering technological solutions.
a. Is your proposed change important to the organization?
b. Why is it important?
c. How does it support the strategy?
d. What are the benefits? ROI
e. What is the cost impact? From an implementation perspective as well as from impact to resources, training, time to come up to speed and execution to previous levels
Help the business to succeed

(2) Focus on alignment: Competing messages from the people at the top is the kiss of death for a change initiative. Important change initiatives will always cross the boundaries of groups, departments, and divisions. Creating and sustaining agreement among key leaders may be one of the most important factors for successful change
Help the leaders manage their business, ensure that they are successful

(3) Focus on stakeholders. The stakeholders are the resources who will have to adopt and execute the change.
Don’t underestimate stakeholder management! Socialize the idea first, gain their acceptance and then engage them throughout your project from requirements gathering, design of business process/systems, get ideas on how they could make your change better, training needs, method for delivering training etc. this engagement will ensure that they feel that they are the customer and that this change will indeed help improve their day to day functions.
Help the organization (resources) to succeed

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"