Skip to main content

Are you delivering value to the Customer and Organization?

Delivering value to the Customer and Organization:

Ask below question to your self to find the answer.

  1. When we are delivering Product or Service?
  2. Are we delivering value? 
  3. To whom we are delivering value?
  4. What value we are delivering?
  5. When we are delivering value?

All  the above questions are answered in two context, one is customer happiness and organization's ROI ($).

All companies ultimately come down to one element i.e.: MONEY.

When customers are happy, good culture, process followed for the quality and timely delivery of the product or service will make (and save) us more money.

As a Manager we are in the business for generating money for the customer and improving customer satisfaction.

Both are relevant and connected.

The actual value will be delivered during every release (scrum), as mentioned in the below chart.

As a (Project/Product/Program) manager we need to work on below activities:
  • Creating roadmap
  • Business cases
  • Analyzing the industry and competition
  • Product strategy
  • Product launch
  • Auditing results
  • Sustaining product
  • Re-engineering product
  • Product retirement
You should recognize that the value should be delivered to the customer at the earliest. Using "Scrum" makes this more evident. Refer above chart.
 
Below value metrics will help you to create value:
  • Revenue
  • Investment
  • Operating cost
  • Profit
  • Customer satisfaction
  • Employee satisfaction
  • Repeat customers
  • Customer referrals
  • Time to market
  • Growth
  • Market share
  • Market drivers (conducting events, roadshow, royalty program, gift coupons, campaigning)



 

Comments

Popular posts from this blog

New way of product development

Today is the era of fast-paced world and competitive world. Companies are realizing that the old sequential approach to developing new products won’t get the job done and product can’t be reached to market when compared to competitors. The 4 stages of product development are as follows – R&D, Growth, Maturation, and Decline. Instead of sequential approach, companies are using holistic approach – as in rugby game, the ball gets passed within the team as it moves as a unit up the field. This holistic approach has six characteristics: 1)     Build-in-instability 2)   Self-organizing project teams 3)   Overlapping development phases 4)   Multi-learning 5)   Subtle (very clear and strong) control 6)   Organizational change to explore and learning The above six characteristics forming a fast and flexible process for new product development with advantage of act as a change agent, creative, market driven ideas, flexi...

Product Manager vs Product Owner

Both the product manager and the product owner work towards a common goal, to build and improve products that create meaningful value for customers and all stakeholders within the company. This usually happens by delivering and optimizing product features. Product Manager Product Owner The product manager discovers what users need, prioritizes what to build next, and rallies the team around a product roadmap. The product owner is responsible for maximizing the value of the product by creating and managing the product backlog. This person creates user stories for the development team and communicates the voice of the customer in the Scrum process.      Product Manager and Product Owner's work on below vacuum. Product manager focus on: Business Strategy Long term Product Vision Long term Product Strategy Product Roadmap Alignment with Product Owner Product owner focus on: Release Plan (Product Backlog ie: ...

Data & Analytics

Data and analytics is the management of data for all uses and the analysis of data to drive business processes and improve business outcomes through more effective decision making and enhanced customer experiences. Four Types of data analytics: 1.         Predictive data analysis Predictive analytics may be the most commonly used category of data analytics. Businesses use predictive analytics to identify trends, connections between data, and relationship between data. 2.        Prescriptive data analytics Prescriptive analytics is where AI and big data combine to help predict outcomes and identify what actions to take. Prescriptive analytics can help answer questions such as “What if we try this?” and “What is the best action?” You can test the correct variables and even suggest new variables that offer a higher chance of generating a positive outcome. 3.        Diagnostic data analyti...