While there are many types of change programs, 2 primary goals typically drive a change initiative:
Near term economic improvement or
Improvement in organisational capabilities
Harvard Business School professors Michael Berr and Nitin Nohria coined the terms Theory E and Theory O to describe these two goals.
Theory E: An economic approach
The primary focus of Theory E is to immediately increase shareholder value. The same is measured by improved cash flows and share price. Popular notions of employee participation and the ” learning organisation” take a back seat in this approach.
According to Theory E all implicit contracts between the company and its employees are suspended during the change effort. Individuals and units whose activities fail to provide tangible value creation (example: R&D and Planning) are particularly vulnerable in this approach.
The CEO and the executive team along with the help of some external consultants drive this type of change. The various departments, business units and employees of the organisation are like pieces in the managements strategic chess board wherein they are rearranged or combined or occasionally cashed out.
Theory O: An Organisational Capabilities Approach
The goal of theory O change is to develop an organisational culture that supports learning and an high performance employee base. In this approach the companies invigorate their cultures and capabilities via individuals and organisational learnings. This promotes a flatter organisation, encourages employee participation and fosters strong bonds between the organisation and its people.
Implicit contracts in this approach are too important to be broken as this approach banks on employee participation which is quite the opposite of a Theory E approach.
Companies taking the Theory O route don’t subscribe to concentrated power and directions from the top. Leaders that drive Theory O change are less interested in driving the change themselves. They are more focused in developing employee attitudes and behaviours that will sustain the change that they (the leaders) intend to bring.
Theory E or Theory O?
Most companies studied by professors Michael Berr and Nitin Nohria preferred a mix of the two to suit their needs.
The table below explains why
(Image Credit: Harvard Business Review)
So which approach is best for your company? Well, only the people familiar with the inner workings of your company can say with authority. However, you may use the content above as a good starting point.
Named after Enrico Fermi, the Italian-American physicist who created the world’s first nuclear reactor, Fermi thinking is designed to help us to make fast, useful calculations with little concrete information.
It was Fermi’s belief that the ability to make educated guesses when facing unknowns or complex problems was a crucial skill, not just in science but across many domains.
Example:
How many piano tuners are there in Chicago?
Take a minute to think about how you might approach this problem. How do you estimate this quantity without looking up anything online?
At first glance, this might seem like a really hard question to answer without additional information. However, we can produce a reasonable estimate by making a few sensible assumptions.
Let’s say that Chicago has around 5 million people. Pianos are generally owned by families rather than by individuals, and perhaps each family in Chicago has 4 people. Then there are around 1.25 million families in Chicago.
Let’s assume that one in every ten families owns a piano that is tuned regularly. That would mean that there are around 125,000 pianos in Chicago.
How many piano tuners do we need to maintain these pianos? We can assume that each piano should be tuned once per year, so there are 125,000 piano tunings in Chicago each year.
If each piano tuner works 8 hours per day on each weekday, and if each piano takes around 2 hours to tune, then a piano tuner can tune around 4 pianos per day for 250 days per year. That’s around 1,000 piano tunings per piano tuner each year.
So we can estimate that we need around 125 piano tuners to perform the 125,000 piano tunings in Chicago each year.
While we can’t claim this answer is exactly accurate, we can claim that it is a fair estimate of the actual value. That’s the goal of a Fermi estimation problem.
Conclusion
Fermi thinking often requires us to make reasonable assumptions and estimates about the situation in order to come up with an approximate answer.
Also you need to be able to explain and justify what you did when coming up with the solutions like in the example above.
In business, it is often necessary to make quick estimates when neither time nor resources are available for making traditional assessments.
At this juncture, even a gross estimate is very useful to head off ill-advised expenditures, which are unlikely to generate a baseline profit. A back-of-the-envelope determination of market size, costs, or technical feasibility may be needed.
Such a calculation ignores details, focuses only on major factors, and aims at an estimate.
Until recently, business educators interested in teaching students to use Fermi questions would find it difficult to locate published questions related to the business world. Fermi questions and their solutions tended to involve physics, chemistry, biology, and other so-called hard science
However, this may be changing as the trend is for consulting firms and corporations such as Google and Microsoft to ask applicants to try to answer Fermi questions, as part of the job interview process, with the goal of identifying creative thinkers
Moravec’s paradox is the observation by artificial intelligence and robotics researchers that, contrary to traditional assumptions, reasoning requires very little computation, but sensorimotor skills require enormous computational resources.
The principle was articulated by Hans Moravec, Rodney Brooks, Marvin Minsky and others in the 1980s.
Moravec wrote in 1988, “it is comparatively easy to make computers exhibit adult level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility”.
Hans Moravec laid the basis of this paradox and considers one possible explanation to be rooted in evolution.
Evolution has taken millions of years to evolve the current sensorial abilities of humans.
Some examples of skills that have been evolving for millions of years: recognizing a face, moving around in space, judging people’s motivations, catching a ball, recognizing a voice, setting appropriate goals, paying attention to things that are interesting; anything to do with perception, attention, visualization, motor skills, social skills and so on.
These skills that we possess are mostly unconscious and come to us without any thought; we seem to do them without any strain, making what looks difficult to be fairly easy. These unconscious processes are difficult to reverse-engineer and teach to the computers, thus increasing the complexity of the problem.
Some examples of skills that have appeared more recently: mathematics, engineering, human games, logic and scientific reasoning. These hard things that we make computers solve are based on a deliberate process we call reasoning. This process is conscious, one of abstract thought and closely related to brain functions in humans that have evolved recently (less than 100,000 years ago) in the context of the long evolutionary process.
A compact way to express this argument would be:
We should expect the difficulty of reverse-engineering any human skill to be roughly proportional to the amount of time that skill has been evolving in animals.
The oldest human skills are largely unconscious and so appear to us to be effortless.
Therefore, we should expect skills that appear effortless to be difficult to reverse-engineer, but skills that require effort may not necessarily be difficult to engineer at all.
Human & Machine Augmentation
Despite the huge amount of enterprise data available, half the picture is missing. Systems of records like ERPs only record what happened. And what happened is the results of human decisions made “outside” systems based on a context which can soon be forgotten or lost.
Example: You detect an oversell situation and expedite replenishment, but due to external factors some customers are cancelling their orders, and you end up with excess costs and stocks. A bad outcome for the replenishment decision, and a lesson to remember if it happens too frequently.
The real world is different, and context can make a lot of difference. We’re able to assess and understand context (because of evolution) in ways that machines cannot.
The lesson for the business world is that utilizing AI is not just about replacing manual work by computation. Instead, it’s about respective augmentation between humans and machines – leveraging each other’s strengths, timely and consistently.
We sense danger, threats, rewards and apply judgment, unconsciously most of the time. We make decisions based on context that may violate rules or convention – sacrificing the queen at chess, driving through red light if necessary, or expediting a drug by helicopter for a life-threatening emergency.
With a human/machine augmentation model, we are moving from people doing the work supported by machines to machines doing the work guided by people.
It’s not about us v/s them
The concept that humans and machines have different strengths played out in a research from Harvard. In the study, a breast cancer detection algorithm was able to detect cancer cells 92% of the time. However, the doctors were able to identify cancer cells 96% of the time.
This clearly shows that humans are better, right? But wait—the next finding was perhaps the most telling part of the study. By combining the algorithm with human experience and intuition, the team was able to identify more than 99% of cancer cells. This blending of strengths of humanity and technology points to an incredible opportunity to solve the most complex problems that the world is facing today.
The idea that “technology will fix things” is misguided.
Machines expertly handle repetitive and automated tasks and will always be faster and more precise. They might be good at tasks closely related to brain functions in humans that have evolved recently(Algebra, Logic, Abstract Thinking etc.), less than 100,000 years ago, in the context of the long evolutionary process.
However Technology cannot fix bad processes, poor management practices, or failing employee morale. Without people, there is no innovation, no strategy and no connections with customers.
The uniquely human skills of creativity, innovation, adaptability, empathy, integrity, and imagination which have evolved over a million years are becoming increasingly critical to success, and these skills cannot be taken over by machines.
The new era is going to be about the handshake between humanity and technology wherein machines will be doing the work guided by people.
55% of all CRM projects don’t produce results, according to Gartner Group, a research and advisory firm.
In 2017, CIO magazine reported that around one-third of all customer relationship management (CRM) projects fail. That was actually an average of a dozen analyst reports. The numbers ranged from 18% to 69%.
So how do we define CRM?
CRM aligns business processes with customer strategies to build customer loyalty and increase profits over time. (Note the absence of the words “technology” and “software” in the above definition.) CRM is not a software tool that will manage customer relationships for you. The CRM software is just a conduit that connects an organizations customer strategy and its processes with the goal of improving customer loyalty and increased profitability.
5 Critical Reasons why CRM projects fail
Lack of a Robust Customer Strategy: For a CRM program to succeed, you first need to create a robust customer strategy. Identify which customers you want to build relationships with and which you don’t. Every customer is unique and has a different current and potential value to your company. The outcome of your customer strategy should be customer groups spanning from the most profitable to the least profitable. For the most profitable customers you need to identify ways and methods to broaden and deepen the existing relationship and for the least profitable you need to decide if you really wish to serve them at all. This segmentation is crucial and it is done to achieve specific marketing goals.
Poor Business Process Design: Without business process improvement, you’re just creating another place to enter data. The predictable result is that users will be unimpressed, software utilization will be low and user adoption will steadily wane as users work outside the system using spreadsheets, shadow applications and manual methods. Staff productivity is enabled with technology, but not achieved with technology alone. Business process automation is the #1 contributing factor to increased employee productivity. Some common business process themes to consider along with your CRM strategy would be Quote to Cash, Lead to Customer and Procure to Pay or Record to report. It’s important that an organisation performs process optimisation before cataloging their CRM requirements. The new business processes will introduce new CRM requirements that will otherwise be missed if the CRM requirements are drafted looking at only the existing processes.
Too Much at Once: Trying to do everything at once guarantees that you won’t do any of it well. You end up with chaos and confusion rather than the more efficient business processes you imagined at the outset. Divide your CRM implementation into phases to make the project more manageable. You can work on multiple aspects of your implementation at the same time. Just don’t try to complete the entire enterprise-wide implementation all at once.
Business and tech teams don’t work together: Every department in your company plays a vital role in the overall success of the business. At the same time, these departments also have their own priorities, considerations, and ideas about how to tackle any given problem. When a project comes along that crosses through multiple departments — like a new CRM — one of the biggest hurdles to success is often getting these teams on the same page to reach a mutually beneficial solution. This often means breaking down departmental barriers, freeing data from dedicated department silos, and creating uniform (or at least consistent) processes for accessing and using customer information. Your business and tech teams will need to work together in new ways to make sure that everyone is getting the most from the CRM software.
Lack of user adoption: It can be challenging to accept change, especially when it comes in the form of a new CRM, with new processes, responsibilities, and a steep learning curve. Implementing a CRM means shifting the way your sales team organises its contacts and prioritises its work, which means there could be quite a bit of resistance to this type of change. Users need to be convinced that their old data will still be available, that the new product is easy to use, and that training will be provided. Let them know that you understand that there will be a transition phase and that it takes time to get up to speed. You also need to articulate the problems the CRM solves for them as well as the benefits it offers to them. Users don’t care how a CRM system benefits the management so leave those out. Focus on how your chosen solution will automate their processes, save them time, and generate bigger deals. In short, focus on operational productivity rather than management productivity because in the end its operational productivity that drives management productivity.
Conclusion
Even a relatively successful CRM implementation followed by stagnation will result in a steady decline in CRM usage over time. It won’t take long until users and managers begin working without or around the system.
Therefore it is imperative to understand that like business, CRM is a journey, and successful CRM programs leverage continuous process improvement cycles to constantly refine and optimise the business software system.
Last but the not the least, for a successful CRM implementation, an organisations focus should be in the following order
write original, persuasive, natural, useful, informative content - creating content advice - text on a spiral notebook with cup of coffee
Idea in brief
Creating compelling content and copy requires a solid framework. The absence of a solid framework leads to content that is disorganized. This has an impact on the user experience and understanding. Furthermore, it inhibits their decision making with respect to the action that you are expecting them to take after they have consumed your content.
The 4 P’s of Persuasion is a framework to formulate persuasive content that caters to the challenge above.
The Slide Deck
The slide below explains The 4 P’s of Persuasion Framework.
As more of our basic needs are met, we increasingly expect sophisticated experiences that are emotionally satisfying and meaningful. These experiences will not be simple products. They will be complex combinations of products, services, spaces, and information.
Design thinking is a tool for imagining these experiences as well as giving them a desirable form.
In this blog post we explain the 5 phases involved in Design Thinking.
Leadership concept with blue paper ship leading among white
Idea in brief
In this blog post we will share a couple of analytical tools that will help you reconstruct the value that your product/service brings to the table thereby enabling you to create uncontested market space and make your competition irrelevant.
With these tools you will not just change the rules but change the game.
The 2 tools we will be outlining are:
The Strategy Canvas and
The 4 Actions Framework.
The Slide Deck
The slide deck below covers the following:
What is the Strategy Canvas.
The outcome of implementing a Strategy Canvas.
What is the 4 Actions Framework.
What is the outcome of implementing the 4 Actions Framework.
In the traditional selling method, salespeople are trained to align a solution with an acknowledged customer need and to undermine their competitors solution.
Perceptive selling emphasizes that salespeople must lead with disruptive ideas that will make customers aware of unknown needs.
And in this new world, that’s the difference between a pitch that goes nowhere and the one that secures the customer’s business.
The Slide Deck
The slide deck below covers the following:
Traditional Selling.
The current problem with traditional selling.
How does Perceptive Selling solve this problem.
Qualities of a Perceptive Sales Professional.
Partners of the Perceptive Seller within the customers organization.
Bonus Material: A detailed Sales Pitch using the Perceptive Selling Method.
Feedback contact customer service opinion survey business concept review young man megaphone bullhorn
Idea in brief
To improve the website experience and connect with their customers, businesses should not only know what their customers are doing on their website but also why they are doing what they are doing.
With the help of the 3 survey questions businesses can merge the customer’s voice with the clickstream data and make better decisions to improve the online experience of their customers.
To identify actionable insights businesses need to marry the what with the why.
The Slide Deck
The slide deck below covers the following:
The irony of data.
How Clickstream Data covers only the what and not the why.
Lists the 3 survey questions which every website must have and explains the benefits of each.
The Jobs To Be Done Framework (JTBD) makes you focus on the underlying job that your customers are trying to complete with your product or service.
Customers buy things because they are facing a problem they would like to solve. With an understanding of the “job (problem)” for which customers find themselves buying a product or service, companies can more accurately develop, market and sell products thereby enabling their customers progress in specific circumstances.
Because the JTBD framework focuses on the causal driver behind a purchase, we can determine why our customers make the choices they make.
The Slide Deck
The slide deck below covers the following:
What is the Jobs To Be Done (JTBD) framework?
Example.
Typical structure of a job which any customer aspires to complete.
