Showing posts with label Roadmap. Show all posts
Showing posts with label Roadmap. Show all posts

Wednesday, 15 September 2021

5 Key Aspects to Overcome Project Roadblocks

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Is there really some documented key aspects we need to follow when it comes to project management? Can’t I do it in my own way?

When you have been just assigned to a project as a project manager, you may ask yourself this question quite often. 

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And that is completely relevant too! If you have got no unique style of handling a project, why would your fellow teammates follow you?

Well, let’s analyze it with a simple scenario. Let’s suppose, you plan to cook Pasta. Now, you can cook it with white sauce, red sauce or pink sauce. You can put chicken, meat or vegetables. But no matter which recipe you are going to follow, you still need to use Pasta, Chicken Broth, Pepper Powder and a few more necessary garnishing to it. Right?

Handling a project is kind of similar to this only. You can do it in your own style, but there are some key elements in the project management those you need to remember always.

In this blog, we’re going to tell you about the main key aspects of project management. Make sure to drop a comment below about what would you like to hear from us regarding project management.

Essential Aspects of Project Management:

There are a lot of aspects to project management. They can vary from project to project and organization to organization. But, the vital factors of project management remain the same.

Here are the top five aspects we would want you to look after in order to your next project’s success:

1. Clear Goal:

Walt Disney once said, “Of all the things I have done, the most vital is coordinating the talent of those who work for us and pointing them towards one certain goal.” 

Now, the entire world can see how that panned out for him. Don’t you think you, as well should do the same thing?

At the starting of the project, you should set a clear goal for yourself and make sure that the goal aligns with the client requirements. Once you set both your short term and long term goals, you need to make sure that each and every teammate of yours have the same goal in mind and working towards achieving it. The short term goals should be aimed towards the tasks to be done by the team. The long term goals should be aimed towards the end result that a project wants to accomplish.

Once you are set with your goals and you know what you want, one of the important project management objectives is already served!

2. Scopes Of Your Project:

In the field of project management, the scope is defined as a set of boundaries that define the scale of a project. It describes the end result which is supposed to be delivered to the client. 

Once you understand the scope of your project, it helps you to understand what falls inside the boundaries of the project and what does not. Activities that fall inside the boundary, are “in scope” of the project. Activities which do not, are mostly “out of scope”. 

Whenever you detect an uncontrolled growth in a project’s scope, it’s scope creep. It usually happens when you add a module to your project, scope creep happens.

Scope creep can increase the resources of the project. Hence, having scope creeps in the middle of the project can be risky. 

Having a clear understanding of your project’s scopes helps you to avoid scope creeps.

3. A Good Project Manager:

We don’t need to emphasize this one much, as we published an entire article named: Key Points Which Make or Break A Good Project Manager based on this previously.

Still, to brief it out to you again, if a project can be compared to a blood circulation system, the project manager should be compared to the heart. So, just like the blood circulation stops when the heart stops working, the project too will be dead if it lacks a good project manager. 

The project manager is the one who sets the goals, strategizes the entire roadmap, and plans out resources to take the project ahead. 

Geoff Reiss, a project management author, once said: “Project management is like juggling three balls: time, cost and quality.” This statement sums it all. Doesn’t it?

4. Engaged Stakeholders:

People who are not a part of the project management group but share a vested interest in the project along with the team members are the stakeholders of the project. 

The stakeholders are not involved with the project like the other team members or the project managers but will be on loop for critical decisions and the overall progress of the project.

So, you see, since they are not involved in the day to day activity of the team, they won’t be really able to understand what your team is doing. Hence, they can’t be involved in every decision of the project, unless you want to turn the project into a battlefield. Neither they can be shut out completely since one of the key aspects of project management is satisfying the stakeholder.

You need to make sure that the stakeholders involved with the project are well aware of the project management objectives so that they are engaged with the project in order to understand it.

5. Dedicated Project Team:

“Get the right people. Then no matter what all else you might do wrong after that, the people will save you. That’s what management is all about.”- said Tom DeMarco, an early developer of structured analytics.

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If you have handled a project management team before, then you know how true the statement is. If you have a dedicated team, your project is already halfway successful. Once your project team is well aware about the short term and long term goals and their responsibilities to reach them, another half too will be over soon!

Once you choose your team according to the project goals, it’s easy to divide responsibilities since the goals align with their skill set. Try doing that once!

Source: novelvista.com

Saturday, 2 November 2019

Creating a DMAIC Pathway for Innovation

On the surface, the DMAIC roadmap and the concept of innovation appear to be mutually exclusive ideas. At least that’s what many critics have claimed is the Achilles’ heel of the Six Sigma methodology. Six Sigma and innovation, after all, tend to personify a natural tension that exists within quality-enhancing activities at any organization – a tension between exploitation and exploration.

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The general wisdom holds that Six Sigma is an “exploitation” activity, while innovation is usually associated with “exploration.” When I speak of exploitation, the term is not being used to describe the act of gaining advantage through unfair means. Instead, it is to transform an organization’s inputs into profitable outputs under its existing business model. As for exploration, the term here refers to the organization’s efforts to pursue new potential business models, novel product or service areas, or both. In short, the former is concerned with current practices, while the latter focuses on discovering new ideas.

However, innovation and Six Sigma do not need to be combatants. In fact, they can act as compatriots; and in some cases Six Sigma can actually be seen as an innovative approach. To get a better understanding of innovation and it complex, ambiguous relationship with Six Sigma, it helps to dig deeper into the definition of innovation. As I see it, innovation transforms the useful seeds of invention into widely adopted solutions that are valued above every existing alternative.

Shared Goals, Different Outcomes


Both Six Sigma and innovation have a distinguished history. The concept of innovation dates back nearly 500 years, as a derivation of the Latin term innovare, which is interpreted as “to renew or change.” In the modern era, the most-often-referenced godfather of innovation is Joseph Schumpeter, a 1930s-era economist. Meanwhile, Six Sigma has been used by organizations for more than 25 years after getting its start at Motorola and being popularized by GE and other corporations.

Regardless of the differences in approach of these methods, most people can agree that both Six Sigma and innovation are focused on improvement. However, while Six Sigma is based on decreasing variability, innovation focuses on increasing value. Sometimes an increase in quality through a decrease in variability does create increased value for the customers; sometimes it doesn’t.

How could increased quality through and decreased variability not lead to an increase in value? The key lies in the “widely adopted” terminology of my innovation definition. New solutions may provide an increase in value that is obvious to the inventor, but not to the customer. The customer may even perceive the new product or service as a decrease in value, which, in turn, will prevent the solution from being widely adopted. This is what can keep a mere invention from graduating into a true innovation.

This discrepancy in perception between the inventor and the customer is why things like the incandescent light bulb and the traditional mousetrap stay around for so long, despite the introduction of other potential solutions.

Natural Conflict


While Six Sigma and innovation are not mortal enemies, there are some key differences between them that create natural conflicts. These differences require managers to remain vigilant about how they should merge the use of these two approaches (if at all) in their organizations.

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The main tension between the two approaches is that Six Sigma requires accurate measurement. How else but through measurement will you know whether a Six Sigma project has resulted in decreased variability and a sustainable improvement? On the flip side, the more radical or disruptive an innovation project is, the more difficult it will be to measure accurately the expected risk of the project and the projected profitability and adoption possibilities.

A great example of the difficulties of forecasting risk and outcomes is the Segway transportation device. Imagine you were in charge of the project back in 2000. How would you size the market? How would you forecast the media response? How would you estimate the risks to the project posed by sidewalk regulations? How would you measure consumer readiness?

Most forecasts for new products or services are based on old forecasts, a naturally flawed measurement approach. However, forecasting simply loses all credibility when it is applied to disruptive innovations. This inherent uncertainty is why successful innovation is often the result of asking the right questions, while success with Six Sigma is often the result of finding the right measurements.

The mindset created by the need for accurate measurement is congruent with typical executive thinking, which brings me to another common tension in business – that between the executive and the entrepreneur. Mismanagement of this tension is one of the greatest obstacles that prevent organizations from innovating sustainably.

Let’s compare these two mindsets:

◈ The Executive Mindset – Executives typically are focused on what they can do to avoid failure. They tend to focus on doing everything they can to make the trains run on time, so to speak.

◈ The Entrepreneurial Mindset – Entrepreneurs typically are focused on trying to do whatever they can to create success. When faced with train delays, entrepreneurs tend to ask, “Why take a train?”

These natural tensions mean that managers have to be careful when implementing Six Sigma in some of the more creative aspects of the business. Otherwise, there is a real possibility of stifling the unstructured thinking in areas such as design and research and development (R&D), where partial ideas need to be collected and connected to form strong innovation candidates.

DMAIC for Innovation


Although managers must take care in implementing Six Sigma in the more creative aspects of the business, there is a way to implement the DMAIC roadmap within these functions. I have stretched its usage a bit further and created a DMAIC roadmap for innovation.

Define

Imagine that you work for an automobile manufacturer and you are asked to solve the following technical challenge: “How would you make our automobiles use less gasoline?”

Think about what your approach would be. Some might focus on making the automobile lighter; others might focus on making the engine more efficient. Still others would focus on making the car more aerodynamic, and a few would think about ways to make it ran on something other than gasoline. The results you get will depend on the innovation questions you ask.

Any successful innovation effort begins with a cross-functional innovation leadership team defining what innovation means for the organization, establishing a common language and clearly communicating this message to the organization. While it is sometimes good to have people going off in many different directions at once, that needs to be a conscious choice; otherwise, the innovation energy of the organization will dissipate and little will be achieved. Defining a common language around innovation will help focus this energy.

Articulating an innovation vision also will help provide this focus. A vision is about the “where” and the “why,” not the “what” or the “how.” Jack Welch, former CEO of GE, once said, “Good business leaders create a vision, articulate the vision, passionately own the vision and relentlessly drive it to completion.” An innovation vision can help employees answer questions like, “What kind of innovation are we pursuing as an organization?” or “Why should employees, suppliers, partners and customers be excited to participate?”

Organizations also must define their innovation strategy. This is not merely an agenda for new product development or a technology roadmap from R&D. Instead, an innovation strategy identifies who will drive a company’s profitable revenue growth and sets the innovation direction for an organization toward the achievement of its vision. A well-defined innovation strategy helps the organization define which innovation challenges to focus on and what tactics will best help the organization conquer those challenges. At the same time, it serves as a map to refer back to as projects and ideas are being evaluated, so that, ideally a link can be maintained between the organizational and innovation strategies.

Measure

While it is often harder to estimate the market size for true innovations than it is for line extensions or product improvement projects, it is still important to measure certain things related to innovation. Here are some key innovation measurement questions that need to be asked:

◈ What are the organization’s innovation goals?
◈ What is the capacity for innovation in the organization?
◈ What is the organization’s appetite for risk?
◈ How will the organization finance innovation projects?
◈ How will the organization measure the innovation’s success?

Analyze

Innovation requires a great deal of analysis. This includes analysis of the key insights from which the team generates ideas; analysis of the brand equity and capabilities of the organization that can be leveraged; analysis of what direct and adjacent competitors are doing now; and analysis of the future strategic actions that competitors are expected to take. In completing this analysis, it is useful to use a methodology like Rowan Gibson and Peter Skarzynski’s four lenses from Innovation to the Core (Harvard Business Press, 2008):

◈ Challenging orthodoxies: Questioning deeply held dogmas inside companies and inside industries about what drives success.

◈ Harnessing discontinuities: Spotting unnoticed patterns or trends that could substantially change the rules of the game.

◈ Leveraging competencies and strategic assets: Thinking of a company as a portfolio of skills and assets rather than as a provider of products or services for specific markets.

◈ Understanding unarticulated needs: Learning to live inside the customer’s skin, empathizing with unarticulated feelings and identifying unmet needs.

The Analyze phase is not simply about generating insights; it also is about generating the ideas. When it comes to innovation, people don’t always realize that their “great ideas” are actually only partial ideas. So, another part of the Analyze phase, when it comes to innovation, is the connection of partial ideas to create potentially complete solutions. During Analyze, there also is a great opportunity to take these raw ideas and make them better. The crescendo of this phase is the analysis of all of the potential ideas, their evaluation by cross-functional teams and the final picking which ideas to fund.

Improve

The Improve phase is about getting down to business, developing the selected ideas and creating the actual innovation. This includes prototyping, market testing, customer feedback and – most importantly – learning and iterating. A key part of this iteration is finding the right questions (and answers) to highlight reasons for potential market success or failure.

But there is another part of innovation that is often under-appreciated: the role of communication. When bringing an innovation to market, an organization also is bringing new value to customers that they may not understand intuitively.

Too often, companies fail at innovation because they ignore the importance of communication. How can you contribute to the improvement of an idea if you don’t understand what it is or the magnitude of its impact? Internal communication can help turn employees into passionate believers and supporters of the ideas. Externally, communication can help explain the new value for an incremental innovation, or to educate the customer about the value of a disruptive innovation.

Control

Control is about making innovation repeatable, sustainable and successful in the organization. How do you make innovation a deeply embedded capability of the organization? The organization must move from pursuing a “firefighting” approach to innovation and instead create a continuous process with organizational commitment at every level.

Organizations can work to build a company culture with improved tolerance for risk and an understanding that failure is a real possibility. Instead of avoiding failure, innovative companies seek success and mitigate failure through a portfolio approach (working on a collection of strategically similar projects at once) and by embedding an ability to learn fast from failure or success.

Other methods to ensure that innovation is ingrained in an organization’s core values include:

◈ Building an organizational structure and policies that enable resource flexibility and movement of resources to projects where they are needed most.

◈ Creating a culture that supports the free flow of information to employees about customer insights and the value of innovation.

◈ Providing the leadership commitment, the processes and tools, the rewards and recognition, and the skills training necessary to create a sustainable innovation process culture.

Working Together

Six Sigma and innovation can co-exist. While the terminology of each approach may differ, it is possible to create a shared vocabulary and a shared understanding of how the two methods of creating positive business change can work together. The key is to find the proper balance between chaos and structure, exploration and exploitation.

Innovation and Six Sigma actually have a lot in common. To achieve high levels of quality and continuous innovation, practitioners of both methods require commitment and a professional approach. If you can embed quality into your products, you can also embed innovation into your organization.

Friday, 16 February 2018

Comparing and Contrasting IDEAL and DMAIC

Comparing and contrasting the way different disciplines and tools map to one another can help lead to a better understanding of each of the things being compared. This paper reviews a methodology called IDEALSM, which was developed and evolved by members of the Software Engineering Institute (SEI), and compares it with the Six Sigma DMAIC roadmap and thought process. After a brief review of IDEAL and DMAIC individually, this article examines ways they are similar and ways that they might challenge and inform one another.

The Software Engineering Institute and IDEAL


The SEI has long fostered work in software process improvement (SPI). In response to requests for more guidance selecting among improvement alternatives and getting improvements readily adopted, a team developed the first incarnation of IDEAL in about 1993. The roadmap and substantially current model of the process took shape in about 1996 (Figure 1).

Figure 1: IDEAL Model

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In a nutshell, the IDEAL acronym and key activities at each stage can be summarized as follows:
  • Initiating
    • Understand the improvement opportunity and its context and potential business value.
    • Identify stakeholders and the first view of the infrastructure scope and risks that would be required for successful transition of the improvement.
  • Diagnosing
    • Describe the current and desired states.
    • Explore the opportunities and solution alternatives.
    • Develop recommendations.
  • Establishing
    • Identify tasks and responsibilities.
    • Set priorities.
  • Acting
    • Pilot the improvement.
    • Learn from the pilot and refine the plans.
    • Implement the refined improvement.
  • Learning
    • Monitor and control the ongoing inputs and outputs.
    • Diagnose early warning signals and adjust and control as needed.
    • Learn from the ongoing process and make next recommendations.
One can see at a glance that IDEAL is constructed in a way that presumes at least an initial sense of a solution at the outset. That is likely one reason that IDEAL is often referred to as a transition process (more than a problem-solving process).

DMAIC – Quick History


For Six Sigma Belts, depending when they were trained in Six Sigma, they may or may not see DMAIC as having been a core element from the beginning. In the early days, there were the Six Steps to Six Sigma and then an evolution to MAIC as the core roadmap and methodology. As teams underlined the importance of understanding the problem and related goals and scope, a Define stage (D) was added to make DMAIC for many companies. An outline view of DMAIC is provided in Figure 2.

Figure 2: DMAIC Overview

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Strength vs. Weakness Orientation


IDEAL is strength based, meaning that it focuses on improvement ideas and an ideal state, driving the planning, piloting and ongoing control connected with bringing that improvement to reality. DMAIC, in contrast, is inherently weakness based, meaning that it focuses on reducing costs or cycle time, driving the use of facts and data to uncover causes, and only then does the focus swing to solutions and implementation.

At first, this distinction may seem a little arbitrary. After all, a strength-based project goal like “improve customer satisfaction” and a weakness-based one like “reduce complaints” are just two ways of saying the same thing. While that may be true on the surface, there are implications that the choice of one over the other can have on the way a team thinks about data and learning.

Increasing yield, which is listed in Table 1, is a good example of a strength-based goal that was popular at Motorola before Six Sigma. Since yield is the proportion of units that survive a manufacturing process ready to ship, it summarizes performance. If yields suddenly dropped from 90 percent to 70 percent, the numbers do not provide much diagnostic help to see where the problem is or what to fix. Strength-based goals encourage a team to lean toward ideas (about how to improve the strength) and the future state.

How might things be different for a team setting out to reduce defects? First, their view is more detailed. They are looking at the defects within the units. This was the most fundamental shift that Six Sigma brought to Motorola. This team would tend toward facts and data (What are the defects? Where are they happening?) instead of improvement ideas. Their metrics would be more diagnostic. When defects of a certain type move from one per week to three per week, there is some information about what is wrong and what to fix.

A last contrast to make involves the reporting climate in an environment. People know when their bosses want to hear good (strength-based) news, and they tend to put the “best face” on data being reported at all levels. This can submerge and subdue details, sometimes to the point where leaders don’t see details that could have previewed or mitigated trouble that surfaces larger and later. On the other hand, companies that see the value in weakness orientation invite the details and the gritty dirty laundry in order to get down to fundamental causes and drivers at every opportunity.

See how that distinction plays out as the discussion of IDEAL and DMAIC continues.

Table 1: Weakness vs. Strength Orientation in Problem Solving

Weakness Strength 
Example Reducing defects
Reducing complaints
Reducing delays
Increasing capability, yield
Increasing % satisfied customers
Increasing throughput
Use of Metrics  Diagnostic metrics
More detail: Defects within units
Details support root cause analysis
Performance metrics
Less detail: Defective units
Rollups that summarize performance
Focus of Team Facts, the past and present
What are the defects?
Where are they being found?
Ideas, the future
What can we do to improve customer satisfaction? 
Impact on Reporting Surfaces real issues
(Dirty laundry okay)
Focuses on improvement
Good news tends to filter out detail, favors the best spin 

Table 2: Summarization of IDEAL and DMAIC Similarities and Differences

IDEAL   Comparisons and Contrasts DMAIC
Initiating Set context

Build sponsorship

Charter infrastructure
IDEAL begins with a stimulus for change. While IDEAL and DMAIC seek to quantify business impact and align sponsors, IDEAL may focus more on the benefits of implementing an improvement that is at least partly in view at the outset.

DMAIC discipline focuses first on understanding the problem (to avoid jumping to a solution).

DMAIC emphasizes the importance of results measures and targets.
Charter – goal statement; business case

Survey the problem and its context – processes; requirements 
Define 
Diagnosing Characterize current and desired states

Develop recommendations 
While nothing would stop and IDEAL team from applying some of the DMAIC rigor to identifying prospective causal factors, building trustworthy measurement systems and gathering facts and data shed light on what is going on. There is not a lot of specific guidance about that.

DMAIC brings graphical, statistical and logical tools and infrastructure for guidance in their proper use (with the Belts system).

DMAIC pays strong attention to holding off on solution thinking and recommendations until there has been some real fact-based learning about the causes or drivers that can be verified to influence the project results measures.
Identify factors and causes that may be influential.

Challenge the measurement systems that will be needed to convert raw events into useful facts and data.

Gather facts and data to shed light on root causes and drivers.

Use (patterns and contrasts in) the data to learn what is driving the project Ys – the critical results measures.

Verify key causes and drivers.
Measure
Analyze
Establishing Set priorities

Develop approach

Plan actions
DMAIC brings discipline about not jumping to a solution or even into the solution selection process by paying attention to the breadth of alternatives and the rationale used to select among them. General solution

Alternatives
Improve
Acting Create solution

Pilot/test solution

Refine solution

Implement solution
Considerable common ground here.

DMAIC brings some useful discipline and guidance about creating an effective transfer plan.
Select best solution

Pilot the solution

Refine the solution

Plan to transfer control
Improve
Learning  Analyze and validate

Propose future actions
IDEAL pays considerable attention to the ongoing learning that is possible – and necessary – during the implementation and ongoing monitor/control of a particular improvement. That broad view of learning could be helpful to supplement the DMAIC view, which is often more narrowly focused on measures-based, statistical views of control. Track the ongoing stability and success of the transferred process.

Learn from the process – to do DMAIC better next time.
Control

Summing Up


IDEAL is a strength-based transition model because it focuses early on desired state and developing recommendations. From there it devotes much attention to the solution planning, piloting and learning from results.

DMAIC is more weakness based, focusing on the problem (defects, delays, etc.) and the facts connected with it. More visible emphasis is placed on using measures to really get to the bottom of the problem (root cause and Y = f(x) dynamics). Nothing would stop a team from doing this under the Diagnosing stage in the IDEAL model, but the model doesn’t draw out and enforce that data-driven problem solving as rigorously as DMAIC.

IDEAL places more emphasis on ongoing monitoring and learning, after the solution is in place. DMAIC allows for this and encourages it in the Control phase, but with a focus on transfer of control back to process owners, it leaves the ongoing monitoring problem somewhat up to the reader.

In short, DMAIC could teach IDEAL a few things about front-end/problem-solving rigor and IDEAL could teach DMAIC about ongoing monitoring and learning.

Note: Some guidance on the IDEAL model was taken from The IDEAL Transition Framework – Speeding Managed Change by Tom Kimbrough and Linda Levine.