Mind Your Business

In this blog, we will discuss about:

• Introduction to Business and Process Outcome


• Porter’s Value Chain


• Lenz Framework


• Business Outcome Analysis

                                        

Business understanding is the centerpiece of the Data Science Puzzle. Evey Analysis you do should make business sense.

Business Outcome

• The primary objective of running business and give an indication of Business Health.


• BOs are measurable and non financial indicators.

Process Outcome

• There are several business processes and they individually have


• Process outcome talks about business health of that particular process outcome


• POs should be measurable and non financial indicators.


• Collectively contribute to BOs.

For eg, talking about Mc Donald’s(we are taking assumptions)

             

We can see how process outcomes contribute to business outcomes for Mc Donald’s.

In logistics, we can find that need for having right sized raw material, so that it is never less, nor wasted. Also, we should consider the delivery time, fast delivery will help and keep customers happy.

In Recipe Creation, we should maintain variety in food and also the taste quality should never be sacrificed so that we get repeated orders. 

In the Meal Assembly, quality of the food should always be in the top priority, while maintaining the minimum delivery time. 

Let’s discuss Business Priorities for Dominos and Pizza Hut (we are taking assumptions)

                            

We can see the clear difference in business priority of Dominos with fast delivery and for Pizza Hut for ambience and variety.

Process Hierarchy

Business Outcome can have various processes and so processes can further divide into sub processes.


                                      

Lets, take an example, we are taking example of inbound logistics, keeping the right sized raw material is po1, to achieve it we have su processes, we should have proper inbound delivery, vendor selection, transport from vendor to warehouse. Selection of vendor selection can also have several processes.

If we improve vendor selection then keeping right sized raw material is also improved.

Sub processes also improve Super processes.

Frameworks

Porter's Value Chain


                                  

In this framework, we will consider various factors by dividing in two domains, like, Primary Activities, which are actually involved in taking raw material, delivering, printing, warehousing, transportation, marketing, are all part of this.

Support Activities, which support the primary activities, like firm infrastructure, human resource, IT team, purchasing.

For eg, creating competitive advantages so that no other company canopy them. Amazon has perfection in outbound logistics, which ultimately creates customer satisfaction, and so customers never move to other competitors.

All processes in Intel, are well researched and developed. Intel has created competitive advantages for themselves so that no other competitor can copy them.

Pinch To Zoom Framework



                                 

It is inspired from mobile technology, to zoom in the picture by pinching it.Company’s mission and vision objectives. Accordingly, they will have business outcomes and process outcomes. THere can be sub processes as well, like for marketing there are sub processes such as packaging, branding. Also,we know that the subprocess is improved and it will improve the process and so business outcome. As, to improve logistics then we need to look into the process we have in it, also the sub process. We will consider the sub process which can be improved, as well as process and business outcome.

We will be generating data while improving processes and so the data will define whether the sub process complements business outcome or not.

The LenZ


                                                     

You need to understand various tools, and techniques, to improve one of the factors in this graph, like, increase in revenue, decrease in cost, increase in customer satisfaction, and optimization of risk. For example, in case of risk optimization, if you take no risk then you end up providing a credit card to no one, then also you are not adding value to the organization, or also if you take maximum risk, then you end up giving a credit card to everyone.

Now, you can see the top line define revenue, and increase customer satisfaction.

Top line is revenue, middle line is cost, and bottom line is profit.

Risk optimization will work on both the top line and bottom line, as it saves you cost and improves revenue.

The LenZ + Porter's Value Chain

                                    

Now, we have acknowledged all the bottlenecks and problems, and not we solve those using our data science knowledge. Whenever we solve any problem, we should consider one factor from LenZ. For example, if you are improving marketing then we should consider Revenue enhancement. We should also consider what will be impacted if we provide solutions to the problems.

Business Outcome Analysis

                                            

Discover Phase: Try to gather the problem statements.

For eg, the marketing team can tell you about the problem statements they are facing, either they tell you else you can ask the right question.

Analyze: Analyze key challenge

Marketing team has cost/lead. If we have 1million $ in fb and they are getting 1 lakh active leads, that means cost/ lead in this case is 10$. They are your potential customer, which your sales team has to convert. If your lead increases then there is an increase in efficiency.

There can be a case that your competitors are getting leads for 5$/active lead, so there is a performance issue. Now, we know cost/ lead is high. So, we decide what we should do.

Recommend & Plan: Brainstorm for solution, firstly on pilot or small group.

Now, we can build models, which help in increasing the efficiency and reducing the cost per lead, but we will experiment on small domains, or pilots.

Implement: Implementing Solution

Once we know that our model is working fine we should apply the model to all regions, and the model will reduce the cost/lead and gap if any available.

Monitoring & Tracking: Monitor performance

Once a model has started making decisions for the processes then data scientists have to monitor and track performance against benchmark and previous state level. Other processes can also use the model, and monitor performance. Data Scientists can report effectiveness about the model continuously.