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Author: Xin Li

3 Things Business Analysts Must Know About the Digital Organization

Digital Organization has been a popular term when talking about reforming the Organization with IT technology and exploring the new Business Opportunities.

Here are the 3 things Business Analysts must know about the Digital Organization.

1. What does a Digital Organization mean?

In a Digital Organization, not only the digital capability but also the digital mind-set is enabled and practised through Organization model: 1) Strategy & Leadership; 2) Daily Operations 3) Research Innovation 4) Product & Services, 5) Resource Competency.

li 121317aFigure 1 Digital Organization Model

  1. Strategy & Leadership
    Real-time and meaningful information can form the basis for Strategy analysis and decisions. The Management Team would need insightful overview of the Organization performance and then steer the management effectively. Applications and Analytics Tools are the digital capabilities to support the Strategy & Leadership. 
    More importantly, the Management Team needs to have digital mind-set for setting up the Enterprise Digital Strategy which supports the Business Strategy or even part of the Business Strategy. A Digital Organization requires the steering and commitment from the Management Team.
  2. Daily Operations
    Digital and automated Business Processes do not mean taking off people’s job. It means everyone can access the information more efficiently and take actions more quickly. Everyone is the owner of a piece of information. If there is no Information available or accessible, it is everyone’s own interest to raise the improvement request and share it with others. Any digital issue identified at daily operations could have large impact on the performance of an Organization. 
  3. Research & Innovation
    A Digital Organization can make more profit out of the Research & Innovation with the aid of new insight from data analytics. Research & Innovation is crucial for any type of Industry. Understanding the proper data and making use of it can create new business opportunities. A Bank might predict the investment risks by performing the scenario analysis and create new investment products. An Engineering Service company may provide data product in addition to the services. There is unlimited number of opportunities for R&D to drill down into the data and explore.
  4. Products & Services
    Each Organization provides Products or/and Services. How to achieve the Financial Goal is a strategic question to answer. The strategic analysis of Sales requires the support of all kinds of data: the Marketing Forecast, Competitor Analysis, Budgeting Analysis, etc. In a Digital Organization, from identifying the prospects, till closing the contracts, all the Sales Information needs to be available, accessible and reliable. 
    For the Product Production, the Quality Control Information and Production Process Information can be digitized and automated for efficiency improvement in a Digital Organization. 
    For a Service Provider, the Planning Information, Pricing Information and Logistics Information might be essential for the Business Model. How to optimize them and attract more Clients would require a thorough data analysis in a Digital Organization.
    In a true Digital Organization, new Product or Service might be identified and explored.
  5. Resource Competency 
    In a Digital Organization, the most essential competence is not the Computer skills, but is all about the mind-set and focus on the digitization improvement possibility. The Digitation Need can come from any role within the Organization and the awareness of the Digitization should be promoted within the personnel.

Every Digitization change will bring changes to Personnel’s daily work and demand on the new competence. The personnel will need to get trained for keeping up with the new Digital capability.

2. Digitization Maturity Level Of An Organization

Each Organization is nowadays digitized to a certain level. The maturity level can be rated based on the availability and complexity of the information analytics

li 121317bFigure 2 Digitization Maturity Level

  1. Leve 1 
    Various Business Applications are available to support standard Business Operations in a specific domain; such as a Finance Invoicing Application; a Customer Relationship Management Application (CRM); a Planning Application; a Document Management System.
  2. Level 2 
    The analytics can be done for the individual Application and provides more insight of the Application Data. For example, the overdue Invoice list can be created based on the data in the Finance Invoicing Application. The acquaintance with the clients can be drawn based on the contact records in a CRM system.
  3. Level 3 
    The information of multiple domains of multiple Applications can be integrated and analysed to provide Enterprise-wide insights. For example, the Financial Invoicing Information can be integrated with the Project Budget information to provide the insight of Cost vs. Budget. The Project Planning Information can be integrated with the Project Document Deliverable information to provide more insight of the Project Progress.
  4. Level 4 
    More advanced technology, such as Machine Learning AI, Internet of Things, Big Data can reveal more insights from the huge amount of data, which could even trigger a new Business Model for the Organization. For example, Big Data of all the historical Project Planning information can be researched for identifying the general pattern of Planning, which can be used for automation or optimization.

3. Approach options for building a Digital Organization

First of all, building a Digital Organization is a Continuous Improvement strategy. However, “Rome was not built in a day”. Where to start and how to continue? There are different development-approach options in different dimensions:

Dimension 1 Organization Hierarchy Level: Top-down, Bottom-up

Dimension 2 Scope Complexity Level: Parallel or One-transition.

  1. Top-down: This is the most ideal approach. The Management Team of the Organization gives full support and drives the Digitization development of the Organization. The Digitization Strategy and Roadmap will be part of the Corporate Strategy and Business Development Roadmap. The Digitization Maturity Assessment will be performed regularly to identify the Digitization Improvement opportunities.
  2. Bottom-up: When there is no sponsorship from the Management Team. IT Department will play a very important role in providing Digitization advice to any role in the Organization; can be to Process Owners, or to a Subject Matter Expert. The ultimate goal is however to achieve the Sponsorship from the Corporate Management Team.
  3. Parallel: For an Organization with a complex and huge IT landscape, it is not realistic to change the Digitization Maturity overall at one GO and it is not necessary either. For some Business domains, the Digitization Maturity might be high enough and nothing needs to be changed. To avoid big turbulence in the Organization, a pilot Digitization project can be carried out for applying new Business Strategy and Technology possibilities, while the rest of the Organization remains using the existing Business Process and IT landscape.
  4. One-transition: For a small size Organization with limited number of IT applications, it could be more efficient to improve the Digitization in one GO. The most importance factor for a successful Digitization change is a clear definition of the Business Case with quantified Return On Investment.

If mixing the two dimensions, there are four options, actually three, because option 4 is impossible to succeed.

Option 1: Top-down and Parallel; Option2: Top-down and One-Transition;

Option 3: Bottom-Up and Parallel; Option 4: Bottom-Up and One-Transition

li 121317cFigure 3 Digitization Approach Options

4. Conclusion

Digitization is not a new term at all. It is good to see that more and more Organizations are paying attention to it and most importantly gaining Business Benefits out of it. “A journey of a thousand miles begins with a single step”, just do it and we will be there.

6 Things Every Business Analyst Should Know About the World of Data

You must have heard of Big Data, Data Science, Business Intelligence, Data Driven. Maybe not. What do all these cool words mean for a Business Analyst?

Is there any difference between the Business Analyst and Data Scientist?

1. Definition of Big Data, Data Science, Business Intelligence, & Data Driven

Let’s define each of these concepts

  • Big Data – Big data is high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery, and process optimization. (Ref1-Gartner’s definition)
  • Data Science – It is a concept to unify statistics, data analysis, and their related methods to understand and analyze actual phenomena. (Ref2- Hayashi, Chiko)

    Data Science can include the elements of the following 3 layers:

    Layer 1 – Data
    Layer 2 – Data Analysis
    Layer 3 – Modeling & Evaluation

  • Business Intelligence – Business intelligence (BI) is an umbrella term that includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance. (Ref3- Gartner’s definition)
  • Data Driven – It means that the progress in an activity is compelled by data or decision making is driven by specific data points or results.

2. Concept Relationships

Now that we have defined these concepts, let’s look at the relationships between each concept. Below explains how each concept relates to each other.

  • Big Data and Data Science: Layer 1 Data of the Data Science could be Big Data if Data has 3-V characteristics: high volume, high velocity, and high variety.
  • Business Intelligence and Data Science: Business Intelligence is the implementation of Layer 2 and 3 in the concept of Data Science.
  • Data-Driven Processes and Data Science: The Big Data is created by the Business Processes. The Business Intelligence will serve the Business Processes to improve the decision making and performance.
    The diagram below illustrates the relations between the concepts further:

xin 041117 1

3. The Business Analyst and Data Science

Data Science is intended to create and define the Business Goal and is presented in the most popular CRISP-DM approach (Ref4- Shearer C., The CRISP-DM model shown below).

xin 041117 3

A key part of Strategic Enterprise analysis as outlined in the BABOK (Chapter 6, Page 99) is the creation of a business goal or vision. Business goals and visions are elaborated and defined clearly based on many factors including a data driven approach. Having clear business goals and visions creates a more solid foundation in which programs and projects can be based. Does your project charter contain the data driven results to support the need for the project? A key part of that business case is the data to support the investment.

The first two steps in CRISP-DM requires the good understanding of both Business Process and Data Needs, which is similar to Phase-B and C of the TOGAF circle. Which role can be competent enough for taking care of the first two steps and bridging them seamlessly? I would argue that the Business Analyst is a good candidate for this role as they have the specific skill sets to perform the work of creating specific business goals and visions. In today’s world, the BA typically works just at the project level and rarely gets the opportunity to formulate the business vision and goals. A Business Analyst can then take the vision and goals by using data science to build data sets that support an organization’s vision and goals.

Mckinsey’s report “The age of analytics: competing in a data-driven world” mentions the following “Many organizations focus on the need for data scientists, assuming their presence alone will enable an analytics transformation. But another equally vital role is that of the business translator who serves as the link between analytical talent and practical applications to business questions. In addition to being data-savvy, business’s translators need to have deep organizational knowledge and industry or functional expertise.”

Moreover, the Business Analysts will walk with the “Data Scientists” or any “Business Intelligence Specialists” or “Database Developers” through the whole Data Transformation cycle “Data Collection- Data Preparation/Aggregation – Data Analytics- Deployment.” This team-up is absolutely necessary for ensuring that the deliverable of Data Analytics will meet the Business needs and deliver the associated Business benefits. This is also the Business goal of Data-Driven thing.

Data science can be used at different points:

  • Can be used to create business vision, goals and objectives – creates a need for further Strategic Enterprise analysis or to build a business case for a program or project
  • Can be used to support a project charter or business case – shows the projected value of the project in terms of data, the potential investment needed and the potential Return on Investment.
  • Can be used throughout the project – creates desired state measurements for the project to achieve by further elaborating on data points outlined in the project charter, creates metrics for that can be used to guide the project from initiation to implementation, and finally reports to the project team objectively on how well the project solution design will meet the desired state and business goals.

4. The Data Driven World and TOGAF

TOGAF expresses the Continuous Improvement Concept with a Top-down approach. Data-Driven tries to express the Continuous Improvement with a Bottom-up approach. These two do not have any conflict with each other because Data comes from Business Processes, and the input or output of the Business Processes are in the end presented in the form of Data. TOGAF and Data-Driven approaches meet in the middle.

Such a meeting in the middle can cause a train wreck if both sides are focused on a similar business vision or goals. It’s important to consider the data and its meaning. Two groups can get the same data but draw very different responses. Clear definition of the data points and terms is important to ensure TOGAF and the data-driven world work well with each other.

We can say the Enterprise Architecture is Data Driven. It’s difficult and almost impossible to build the architecture for an organization without at least understanding it’s data. Data Science comes into the picture to fill the gap. Data Science can relate their understanding of business data directly to business vision and goals. Enterprise Architecture needs to understand the business vision and goals clearly to create the environments needed to support the business more effectively.

5. A Fool with a Tool is Still a Fool

Data-Driven does not mean you require a fancy Business Intelligence Tool or vast infrastructure of database warehousing. It means you will need easy access to high-quality data to perform queries, extracts, and analysis. Complex tools may or may not be the answer. Choose your tools carefully to make sure they are meeting your needs.

6. Challenge the Data

Data-Driven means data is challenged. Is this data valid? Is the data of high quality? Should this data be used for decision making? To make a good business decision on data, you must challenge it’s meaning and quality routinely. Don’t take that data set result at face value. Perform data analysis and validate it. When making assumptions, it is important to define those assumptions and communicate assumptions with the data clearly.

All you need to know about the Process Performance Metrics

After defining a new Business Process, how can we measure if the daily work is performed as the process definition?

Then we need Performance Metrics or Performance Indicators. The purpose of measuring Performance Metrics is to control whether the Process is executed successfully and meet the goal of the process. If the Business Process Performance is not good, a follow-up gap analysis can be performed for improvement.

Which Performance Characteristics are meaningful to measure?

A Process is aimed at achieving a goal or purpose. Therefore the Performance Metrics will be all about the achievement of the Process’s goal or purpose. There are several classical Performance Characteristics:

Effectiveness – it indicates whether the goal of the Process has been achieved .

Efficiency – it indicates whether the purpose of the Process has been achieved with the minimum resource (time, money).

Quality – it indicates whether the purpose of the Process has been achieved by meeting the quality criteria.

Timeliness – it indicates whether the purpose of the Process has been achieved in time.

Next to these, some industry-related characteristics can be used. For example, for the Offshore Engineering industry, Safety is an essential core value. So there must be a Performance Metric reflecting the Safety characteristic.

What are the basic attributes for a Process Performance Metric?

In order to define a Performance Metric structurally and consistently, let us first define the basic attributes which a Process Performance Metric should have:

  • ID
  • Name
  • Definition
  • Performance Characteristic
  • Measurement Method
  • Input for the Metric Measurement
  • Output Registration
  • Acceptance Value Criteria
  • Target Value

How to define the Performance Metric for a Business Process?

The definition of a Business Process normally consists of the following elements:

  • the goal of the Process
  • sequential Stages and the purpose of each Stage
  • different Activities within each Stage and the purpose of each Activity
  • inputs and outputs of each Stage

For example, the Package Dispatching Process of a web hand-crafts shop “Hand Made” is like this:

xin 032117 1

The goal of this Process is to send the ordered goods within 24 hours after receiving the Order.

The purpose of Stage 1 is to check the completeness and validity of the Order information: article name, quantity, payment information, client name, billing address, delivery address.

The purpose of Stage 2 is to prepare the package with the specified order.

The purpose of Stage 3 is to arrange the shipping within 24h after receiving the order.

The Process Performance Metrics can be defined either for the whole Process or for each Stage, and even for an Activity. Each Performance Metric represents one or multiple Performance Characteristics.

Continue using the example of the “Hand Made” process; a Performance Metric Example is defined below to show how to define the Performance Metrics on Process and Stage level following the attributes mentioned above:

Example 1 Performance Metric 1 – Effectiveness of the Process

  • ID: M1
  • Name: Effectiveness of the Process
  • Definition: this Metric indicates whether the ordered goods is shipped out within 24 hours after receiving the Order.
  • Performance Characteristic: Effectiveness, Timeliness.
  • Measurement Method: Calculate the difference between the shipping time and the order time.
  • Input for the Metric Measurement: shipping time, order time.
  • Measurement Output Registration: Order Management System.
  • Acceptance Value Criteria: < 24h.
  • Target Value: <22h.

Example 2 Performance Metric 2 – Effectiveness of Stage 1

  • ID: M2
  • Name: Effectiveness of Stage 1
  • Definition: this Metric indicates whether the received order contains complete and valid information: article name, quantity, payment information, client name, billing address, delivery address.
  • Performance Characteristic: Effectiveness
  • Measurement Method: If the completeness and the validity have been checked, rate 2. If only either completeness and validity is checked, rate 1. If none of them is checked, rate 0.
  • Input for the Metric Measurement: Order information
  • Measurement Output Registration: Order Management System
  • Acceptance Value Criteria: 2.
  • Target Value: 2.

How to determine the most important Performance Metrics to measure and monitor?

Since the Performance Metrics can be defined for different characteristics and different levels (Process, Stage, Activity), the total number of Performance Metrics could be huge. It is not realistic to measure and monitor all the possible Performance Metrics. Therefore the Process Owner needs to determine the Key Performance Metrics for the process based on the Business Goal. The Business Goal decides which characteristic of the Performance Metric should be measured. For example, the Business Goal of the Package Dispatching Process is Reduce the total Process time. Then the characteristic Efficiency should be certainly measured. Since the total time is divided into activity level, the performance metrics need to be defined till activity level.

What to do with the measured Performance Metrics?

As mentioned at the beginning, the purpose of measuring the Performance Metrics is to control whether the Process is executed successfully and meet the goal of the process. As part of the Performance Metric Definition, Target and Acceptance Value has been defined. If the Performance Metric does not meet the Target or Acceptance Value, it indicates that the process execution or even the process definition needs to be improved.

So the follow-up for the measured Performance Metrics would be gap analysis finding out what is the cause of the mismatch and what needs to be improved. The Performance Metrics should be regularly measured and improved continuously in case the result does not reflect the Process Performance explicitly. Following the TOGAF’s Enterprise Architecture Framework, the solution for solving the identified process performance gap will be evaluated, implemented and governed.

Xin 032117 2

In a word, in order to achieve the Business Goal of a Process, define the Performance Metrics, measure them regularly, improve the Process Performance and Performance Metrics continuously!

4 Reasons Why I Recommend BABOK and the CBAP Exam

In the 7th year of my BA career, I worked in a Software Company as an Information Analyst. As someone graduated with Master of Science Degree in Microelectronics…

I could not stop wondering about my professional knowledge and skill level in the area of Business Analysts, with the questions like these:

  • How other BAs perform the analysis tasks?
  • Is there a structured framework or knowledge base providing a guideline for various BA tasks?
  • Which knowledge and skills do I need to pick up further?
  • How can I position my BA role in the different type of Projects, e.g. for implementing an IT solution or improving Business Process?
  • How can I prove my BA competence without an academic background in Business Analysis?

Thanks to Google, I found BABOK and IIBA to answer my questions. Have you ever the same questions as mine?

Reason 1 – BABOK Is Like a Mirror for an Experienced Business Analyst

When reading through BABOK, I can directly relate the topics to my daily work. Let us have a quick look at the knowledge areas described in BABOK ®3.0:

Li 031617 1

If using a practical case, it would be so self-speaking why these 6 knowledge areas are important for a Business Analyst:

The Sales Manager raised a request to IT for a better solution managing the Client contact information. What would the Business Analyst do after picking up the request?

  • Make a plan for analyzing the request
  • Execute the analysis to understand the Business problem and need
  • Define the requirements for the Solution concept
  • Evaluate and validate the Solution

And of course, through all the steps, the Business Analyst needs to collaborate with different stakeholders, manage the Requirements and keep a good eye on the Progress and Planning.

Reading through BABOK is like looking at a mirror which reflects on my daily work. My first and second question got answered, and luckily there is no negative surprise.

Reason 2 – BABOK Provides a List Of Various Techniques

In BABOK ®3.0, for each knowledge area, the techniques for carrying out the tasks are also suggested:

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Honestly saying, I don’t know them all by heart. So learning new BA techniques will for sure increase my BA competence. My third question got also answered.

Reason 3 – BABOK Is Created and Updated by Business Analysts

BABOK is a living document and summarizes the best practices of BAs all around the world. It follows the trends and pulses in Business Analyst world. As an Business Analyst, I work in Projects with different approach and topics, such as:

  • Agile Projects
  • Business Process Improvement Projects
  • Data-driven teams
  • IT Architecture

In all different scenarios, it is important for me to position the Business Analyst role and take the right tasks. The Perspectives defined in BABOK gives me either a new idea or confirmation to what I have in mind.

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My fourth question got also answered!

Reason 4 – Take the CBAP Exam

We all know the benefits of earning a Professional Certificate like those mentioned on IIBA’s website:

  • Personal recognition
  • Increased income
  • Professional development opportunities
  • Added Value to your Resume

Besides these, the case study-based questions in the Exam is certainly a nice “Game” to go through. The versatile cases do show the charm of BA career, because it proves a good experienced BA, no matter in which industry he/she is working in, he/she can perform a thorough analysis with the proper approach and technique for different business scenarios.

Although studying for the exam takes a bit time, the new knowledge you will gain and the experience of the exam is certainly valuable and unforgettable!

Till now, all my questions have been answered with a BABOK and the CBAP certificate at hand! How about yours?