Tag: Strategic

Connecting the Dots: The Evolution of the Business Analyst

Written by Wael Altali on October 29, 2019. Posted in Articles.

Last year, I witnessed a product manager trying to figure out how to best market a new product feature.

They were working with a Business Analyst (BA) to make meaning of the multitude of consumer data they gathered. They also worked with an analyst to elicit much broader marketing requirements.

At the same time, a public relations firm was hired to help rebrand the organization. The firm was also working with a BA to collect consumer perspectives on current branding and collect requirements for future branding efforts.

In both projects, the BA did what they had been trained to do. Though they knew what their peers were working on, they failed to “connect the dots.”

The Danger of Not “Connecting the Dots”

The group marketing that new product did not share their learnings with the group working on the public relations strategy. When the strategy rolled out, the analyst working with the product manager noticed some features that contradicted the consumer requirements collected. That analyst said nothing.

In most organizations, we are learning in silos.

Connecting the dots between learnings is not just for streamlining processes and ensuring efficiencies – it is necessary to nurture innovation. Leading creative and strategic projects while also teaching about innovation has validated what researchers have been telling us: innovation is about making connections.

Innovation Through Connections

Connections of information from different sources. Connecting a random idea from an accountant to another random idea from marketing to form an unusual concept. These connections seem simple, but they are not.

They require different segments of an organization to make connections with each other, and to have access to different information that may seem unrelated. There needs to be a systematic and consistent capture of learnings that is not limited to the project, but is organization-wide and ongoing.

Change your Mindset to Change Your Organization

I began to explore different models of how “mindset change” can take place within an organization.

First, mechanisms must be in place to allow for the transfer of information to happen organically. For this, organizations must adopt a continuous learning mindset.

In order to identify the best way to adopt this mindset across departments and silos, I had to identify the common variable that was in all the sessions where connections were missed. A champion of sorts, who has access to information and the skill sets to facilitate connections.

So who acts as the conduit of interdepartmental information flow? This would have to be a centralized person who can connect the dots and “hold the whole” of the organization. A journalist of sorts, that asks the right questions with unyielding perseverance to identify the right problems to solve.

The Business Analyst is a natural fit as the holder of these connections.

BAs have the skills and the access to serve as the internal journalists able to influence and shape strategy. This is especially true for older organizations with mature structures that cause silos between departments without clear collaboration points.

To be successful in such a role, the BA must explore adopting this journalist mindset. Recognizing that there is a lot of information and data, but there is one core story being told.

Perhaps most importantly, it’s their job to uncover that story – not to write it. This story is not necessarily the product solution you are seeking; it is an untold plot that only you are able to see.

Making connections is an essential BA skill to help shape modern organizations. As great entrepreneurs know, connectors get better with practice.

Exercising Forced Connections

Work on forced connections before you are able to make them organically. Fixate on an object in your environment, and use that object to solve a problem. Work on these forced connections to help pivot your brain to start making connections by default. The results can be astonishing.

Free write all the learnings that you have gathered. Are you working on separate projects, all yielding learnings that appear unrelated? Take some time to reflect on those unrelated learnings and begin to write about them nonstop. Do not censor or edit – no one is checking your grammar. Be amazed as connections begin to form without you noticing.

This next technique allows the BA to make connections in real time and I have deployed it repeatedly. After a requirement gathering elicitation session, the BA asks:

“What do I know that they don’t know?”

Is the team missing something that was uncovered in a requirements gathering session eight months ago, or are there gaps that the elicitation with marketing tomorrow could potentially fill?

Recently, I spoke with a BA who told me, “This is great and all, but I can’t keep all this information in my head. How can I reference it more frequently?”

Tools for Consistent Connection Building

I coached her on developing what I am calling a “Connection Board.”

Using a whiteboard, a blank piece of paper, or some virtual tool, draw out three columns. This is a living document that will be updated regularly.

In the first column, write “Discover.” This area is for any information that you are learning that “sticks out.” It makes you think, “Hmmm, that’s not related to this solution, but that’s interesting.”

The next column, titled “Connect”, is for any connections that can be made from the pool of information you gathered under “Discover.” Are there any “dots” that are from very different sources, but seem related?

Finally, move connections you want to investigate further into a column marked “Explore”, and uncover the story behind those connections. What questions does this connection trigger?

This can be a visual board, a chart on a white board, or a notebook entry. It should be easily accessible as a living document to train you on making those connections consistently.

These are some tools and techniques for your toolkit and, there are numerous out there on stretching and exercising your connection muscle.

To fully flex this muscle, we have to stop viewing each product or requirement gathering as a separate event. Often there are connections to be made that your organization needs, but is unaware of their existence. As a BA you have the potential to be a strategy thought leader within your organization, shaping and influencing agendas.

You will find with connection building you are able to reveal ideas that only you have the information to reveal. Working like a journalist is writing small stories – collecting evidence from each story that ultimately connect, allowing you to reveal a breakthrough story.

A Primer on Working with Executives:Swim with the Sharks Without Getting Eaten Alive

Written by Richard Larson on October 24, 2019. Posted in Articles. 1 Comment on A Primer on Working with Executives:Swim with the Sharks Without Getting Eaten Alive

Even though my wife Elizabeth Larson and I owned and ran a business, I wouldn’t exactly have used the term “executive” to describe us.

But, we have both worked with several. And, in building and running Watermark Learning we shared an important characteristic with executives which this series of articles will explore.

Early in my career I was scared at the thought of interacting with executives, much less thinking I could ever be effective or influential with them. I found one executive to be particularly intimidating, and his name was Harvey Mild. He was anything but mild, though. He loved to challenge people and if you weren’t completely prepared, he was the kind of senior leader to figuratively eat you alive. Interestingly, I have a great deal of respect for him thinking back on those days.

A good share of my nervousness early on with executives like Harvey came from an inward focus stemming from insecurity about my work and knowledge. It wasn’t until I gained more experience and learned to focus outwardly when dealing with those in authority positions that I started becoming more effective.

All the areas covered in this series will help you become more focused outwardly on executives rather than inwardly on yourself in your contacts with them. This reversal of focus can change everything about our confidence and effectiveness. It will help us to function more as Trusted Advisors, the best way I know how to be effective with executives.

There are three key points I believe will help you to work more effectively with executives, none of which sound profound on the surface. The first one is covered in part 1 of this series, with the remaining two covered in parts 2 and 3 respectively.

Executives communicate in one of four basic styles and how best to respond to them
Executives can be influenced through our recommendations
Executives make decisions and understanding the process and using techniques will help us be more effective.

All three keys will help you work more effectively with executives and help deliver valuable solutions in your organization.

Part 1. Executives Communicate…Like People

Since executives are people, they don’t all think or act alike, nor do they communicate the same. So how can we best function knowing that? Well, one way is to understand some basic communication styles and make sure we use the knowledge of a particular executive’s style to communicate in a way he or she will respond to best.

Communication Styles

So, what are the basic styles you should pay attention to? Many personality and communication profiles like the one from Insights Corporation use a quadrant system like the one in Figure 1 to depict how we all think, learn, and communicate.

I am assuming most people have seen something like this before. Frameworks similar to Figure 1 are often based on continuums using two variables: 1) whether we are more task or people oriented and 2) if we are internally-focused or externally-focused. Another way of expressing the quadrants is to think about where people get their energy from. We humans are surprisingly consistent in how we fit into one of the categories and how we prefer to communicate. That knowledge can help us communicate more effectively with executives.

Figure 1:Communication Styles, courtesy of and © by Insights Corporation

Red executives are direct, action-oriented, quick to make decisions, and opinionated.

Yellow executives are also direct, but care more about relationships and interactions, need to be involved more so than reds, and like to socialize.

Green executives are reflective sorts, preferring more structured activities than yellows, need time to reflect and think, often consulting with others before making decisions, making them slower and deliberative.

Blue executives on the other hand, are less direct like greens, but unlike greens they are more detail-oriented and focused on facts and research. They similarly need time to make decisions because they want to immerse themselves in the details. They are also opinionated, but in a right-wrong way.

Do you recognize yourself in one of these quadrants or on the line between two? For example, I think of myself as fairly “purple,” having both red and blue energy. And if you are still reflecting on which color you are, it is likely you are a green or blue (please excuse the old joke).

Mirroring

A handy way to use color categories to help you interact more effectively is that of “mirroring,” which you may have heard of.

The concept is meant to remind us to match or “mirror” the style of the person we are communicating with to better relate to them and put them at ease. The best politicians and salespeople use this to help them quickly connect with their prospects. Watch how good salespeople you interact with use this technique.

For example, if a prospect talks quickly, a good salesperson won’t …talk…real…slow. It even extends to body posture. If an executive you are speaking with leans forward, do the same, and don’t lean back in your chair. I recall a sales candidate who I interviewed several years ago. He leaned back during the whole interview while I was leaning forward. His overly casual posture communicated indifference and even a little condescension – needless to say we did not hire that person.

Not only will mirroring put people at ease, but it shows respect and helps build trust too. I don’t mean we should parrot the other person, which is obnoxious. What I suggest is to try and match the tone and emphasis, and also the style and “speed” of the person you are talking to.

For example, if you are dealing with a “yellow” executive style, by all means avoid boring them with details (but make sure they are available if you are asked about them). Or when meeting with your blue or red executive, when should you initiate socializing? As a blue/red, I like to socialize, but prefer to do it after the task at hand is done. If the meeting’s purpose takes the allotted time, I’m fine with little or no socializing.

Handling Executive Colors

See Figure 2 for some tips on handling the various executive communication styles.

Figure 2: Handling Executive Communication Styles

To start employing this first key, I suggest you begin by observing styles, then practice mirroring, both verbally and non-verbally. Look for part 2 of this series for tips and techniques for influencing executives.

Why Agile isn’t Enough Part 4: Lean Startup Learn Phase and BA Techniques that Enhance it

Written by Richard Larson on July 8, 2019. Posted in Articles.

In previous parts of this article, we covered an overview of Lean Startups and its Build-Measure-Learn (BML) methodology.

We also explored the Build portion of the cycle, the first step in a Lean Startup. Another article examined the Measure phase of the methodology, which can provide the measures to learn if our product is on the right track.

Lean Startup was created by Eric Ries and detailed in his seminal book The Lean Startup published in 2011. Lean Startup helps to guide product development, whether in established companies or startups. It is designed to shorten product development time, helping us deliver products and their features that customers need, not just what they tell us they need.

In this part we’ll examine the remaining portion of the B-M-L cycle, Learn.

LEARN

After building a product or features, the second part of the Lean Startup method is measuring how a product is adopted and used. That phase is covered in part 3 of this series. Metrics should be meaningful and should allow us to measure our learning and progress towards goals. Essentially, a Lean Startup grows when meaningful measurements are obtained and then “validated” to provide the learning needed. Validated metrics are those we can learn from to make needed additions, changes, and even “pivots,” which we’ll get back to.

Validated metrics are those we can learn from to make needed additions, changes, or even “pivots.”

3 Things to Learn

Learning is the key to a successful startup, whether that startup is a product or an entire company. Here are 3 important things we need to learn according to the Lean Startup method1:

What customers really need and want, not just what they say they do (in Business Analysis, we constantly strive for that, right?).
Which elements of our strategy are working (or not). That helps the team to maintain the strategy or modify it.
Whether we’re on the right track to delivering a viable, sustainable product or business. If we are on the right track, we persevere; if not, we need to pivot.

And we’re not just talking about any old learning. We need any learning to be validated: backed by empirical data, which results in more useful truths and actionable information than traditional market forecasting or business planning. Validated learning is our best ally in testing and challenging assumptions and pre-conceptions.

Persevere or Pivot?

This question is perhaps the most important one for a Lean Startup. Returning to our B-M-L cycle again in Figure 2 we need to learn if our target metrics are moving our product towards the goals in the initial vision or not.

If the metrics show we are moving toward the goals, then the startup can and should persevere.
If the metrics are not moving us close enough to the target, we can design new experiments to test possible new features. Maybe we were testing the wrong thing. But failing that, or if we cannot generate new hypotheses, it is time to pivot – either by changing the product or to cancel it outright. I can attest that is a difficult decision having had to make it more than once.

Figure 2: Persevere or Pivot in Lean Startup

Examples of Pivots: The Importance of Learning

Did you know that YouTube began as a video dating service with a slogan of “Tune in, hook up”? It did not grow as they had hoped until they discovered the appeal of a general video sharing service they are today.
Groupon started as a platform for rallying people to social and charitable causes but started to fade after some initial success. They added a subdomain that pooled people together to receive discounts and that feature proved far more popular.
In 2004 Yelp was a service where friends could ask each other for direct recommendations for things, which was not moving the company towards their goals. When they learned users were writing reviews for fun, they pivoted to focusing just on reviews that is their business today.

Learn/Decide – 9 Techniques

Besides the Business Analysis techniques to facilitate learning, I’m including techniques in Figure 3 to help with decision-making. That is because the “persevere or pivot” decision is the most important one a startup must make. Business Analysis skills such as facilitation can greatly assist during “pivot or persevere” meetings. Eric Ries suggests startups hold these roughly every month or two1. A suggested focus of these meetings is to review the relevant metrics against hypotheses and consider alternatives.

Figure 3: Techniques for Learning/Deciding

SUMMARY/KEY POINTS

In summary, we’ve seen several ways in which Business Analysis can help fuel a lean startup.

Lean startup methodology relies on the Build-Measure-Learn cycle. It is focused on learning and delivering on what customers really need vs. what they say they do. What could be more important?
Building – focus on finding “problems worth solving” and start by building an MVP, which is the fewest trips through the B-M-L cycle to build a product that provides the most validated learning.
Measuring – valid measurements are the unsung heroes of a successful startup. Without valid measures we can’t learn as quickly or maybe not at all. Remember to avoid “Vanity Metrics” and collect “Metrics that Matter” using AAA metrics –Actionable, Accessible, and Auditable. They are essential to learning what customers need.
Learning – is the acknowledged key to making Lean Startups succeed. We need to learn what customers really need and want, not what we think or what they tell us. We also use that learning to facilitate “persevere or pivot” sessions.
Techniques – there are several proven, standard Business Analysis techniques that can help at every stage of the Build-Measure-Learn cycle. Not an exhaustive list to be sure, but we covered 20 of them and have a summary of the 20 as a free downloadable “template” available on https://www.watermarklearning.com/resources/templates.php.

Finally, if Build-Measure-Learn is the central engine driving a Lean Startup, then Business Analysis techniques and skills are the fuel for that engine. Accordingly, Lean Startups represent an exciting future for those of us who practice Business Analysis.

[1] Eric Ries, The Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses, New York: Crown Business Books, 2011

[1] 5 Big Brands That Had Massively Successful Pivots¸ Published February 15, 2018. Downloaded June 12, 2019. https://www.entrepreneur.com/article/308975

Is AI a Solution, a Technology, or a System…and Why Should I Care?

Written by Elizabeth Larson on June 26, 2019. Posted in Articles. 1 Comment on Is AI a Solution, a Technology, or a System…and Why Should I Care?

A recent article in Harvard Business Review (HBR) asks if AI is a system or is it a solution like so many organizations think?

An interesting question, but one that I would rephrase: Is AI a solution, is it technology that supports the solution, or is it part of a larger system? I have always thought of AI as supporting the digital transformation, which includes all the organizational changes that are needed to make use of digital technologies. So I have always thought of AI more broadly than either a solution or technology. The HBR article points out that 1) 80% of organizations surveyed are developing some sort of AI applications and that 2) companies that think of AI as a system rather than a solution will see their revenues grow by as much as a third over the next 5 years[i].

To understand why this might be the case, let’s consider a few possibilities:

If we think of AI as a solution, we need to be pretty clear about what problem it solves, or business need it addresses. For example, let’s say we need to be able to predict which customers will buy our new product. Sure, this sounds like a business need, but it really is a solution. Ah, you might be thinking., predict customer patterns = predictive analysis, so the solution I need is predictive analysis. No, predictive analysis is a way we can predict who will buy our product. It supports the solution. But what is the business problem? It might have to do with loss of market share, decreased revenues, or a number of other real problems.

So instead of:

Problem: We need AI to remain competitive
Solution: AI

We can think of it as:

Problem: Market share has decreased by x% since this time last year with resulting revenues down by $x
Solution: Ability to predict which customers will buy our new products to increase our customer base and to increase revenues.
Technology needed to support the solution: Software to analyze the data for customer buying patterns and predict customers who will buy our product

But will technology by itself solve our problem? Probably not. What about the related end-to-end processes that will need to change, the massive amounts of data needed to be analyzed and which predictions need to be made, which algorithms to use, the effect of AI on the organizational culture, the jobs that will be created and lost, the business decisions that will need to be made, the business rules to consider and much, much more..

When we think of AI as the technology part of a system, a system in its broadest sense, this starts to make sense. We know that we need to understand not only the technology, but all the context and processes surrounding the technology. When we analyze whole systems, we consider such things as:

Problem: In this case, loss of market share to competitors
Solution: Ability to predict which customers will buy our new product
Technology needed to support the solution: Software to analyze the data for customer buying patterns and predict customers who will buy our product
Processes: current processes and how they will change with the implementation of the solution
New roles and positions to create and hire for

We also know how to make organizations aware of such consequences as:

Wrong staff doing the work, such as creating the models
Dirty data leading to shabby analysis and incorrect predictions
Minimal acceptance by key stakeholders
Wrong people making business rules and other business decisions
Biases built into the predictive models

That’s one of the reasons why, I believe, taking a systems approach increases the chances for organizations to see growing revenues. Thinking of the entire system, not just the technology, allows for the distasteful but essential hard work of figuring this whole thing out. If we look at only the technology, we’re apt to fall into the myriad pitfalls that so many organizations fall into, and which lower the chances of successful outcomes.

How BAs can help

Understand the problem. We can help explain the difference between a problem and a solution in search of a problem and that a solution in search of a problem does not necessarily help an organization achieve its goals.
Ensure data is trustworthy. AI depends on trust-worthy data, data that is clean, that not only has a single source of record, but that comes from an agreed-upon source. That the data business rules are aligned with the organization’s goals and objectives.
Examine algorithms and the underlying data to see if there are built-in biases. BAs these days need to get up-to-speed on AI in its various forms (machine learning, predictive analysis, RPA, etc.). They need to educate themselves on the various algorithms that are used and the advantages and disadvantages of using one over the other from a business perspective. We need to ask really good questions to ensure the right algorithm is being used for the business need at hand. We need to ensure that the kinds of predictions and AI recommendations will not harm the organization’s ability to serve a variety of constituents. We need to look for underlying biases.
Help evaluate predictive tools to weed out any that intentionally or unintentionally promote biases. As BAs we can help the organization examine various measures of success and explain how subjective measures might insidiously shape a tool’s predictions over time. We can look at end-to-end processes and the input to and output from these processes to examine the data for underlying biases. And once we understand the organization’s “system,” we can work with software vendors to help ensure that the software itself is aligned with the organization’s goals and doesn’t have hidden built-in biases.

If, on the other hand, our scope is simply implementing the AI application, much of the needed business analysis could well be short-circuited, resulting in this sorry statistic—72% of executives said their company’s digital efforts are missing revenue expectations.[ii].

Organizations may want us to help them implement AI quickly, but they need us to help them avoid the consequences of falling into the common pitfalls, as so many organizations have done. In other words, we can do our part to help achieve the revenue growth projections when viewing AI as a system

[i] https://hbr.org/2019/05/taking-a-systems-approach-to-adopting-ai Taking a systems approach to adopting AI by Bhaskar Ghosh, Paul R. Daugherty, H James Wilson, Adam Burden

[ii] Gartner, 11/27/2018 HBR, Every Organizational Function Needs To Work On Digital Transformation

Business analysis canvas – The ultimate enterprise architecture

Written by LN Mishra on June 19, 2019. Posted in Articles. 1 Comment on Business analysis canvas – The ultimate enterprise architecture

Business analysis is a fascinating subject.

As business analysts, we need to understand enterprises very well. However, when we look at different frameworks available for business analysis, they seem to be somewhat limited in their scope. Some of them are good in strategic thinking (like SWOT), some of them are good in tactical thinking (Business model canvas, SIPOC, VSM etc.), but there are no frameworks which give us an idea which covers both strategy and tactical aspects.

Business analysis canvas is an attempt to fulfill this need. In this, we are going to start with strategy and go down to the operational level.

Essentially it has 10 core elements and each core element, of course, has sub-elements which we need to understand. Here, we shall go through one by one:

1. Vision / Goal / Objectives
2. External environment
3. Internal environment
4. Strategies
5. Customer management
6. Cost management
7. Stakeholder management
8. Product and services management
9. Risk management
10. Resources

1. Vision / Goal / Objectives

(Financial, Customer, People, Societal, Environmental, Process)
Vision / goal / objectives are essential for any organization to have long-term sustainable growth. Without a vision, it may be difficult for an enterprise to maintain focus. Organizations that do not develop a proper vision or goal usually underperform in the long term.
The organization can set goals and objectives with respect to various aspects such as financial, customer, people, societal, environmental, process etc.

2. External environment

(Competition, Customer, Macroeconomic environment, Regulation, Technology)
The second key element that business analysts must pay attention to is what is happening in the external environment. All businesses operate within an economic environment, which is changing constantly.
Environment essentially comprises of factors like competitors, customers, macroeconomic factors, regulation, and technology.This offers tremendous opportunity, as well as posing threats to the organization. So business analysts must figure out what is happening in the external environment, and how can the organization take benefit of the changes in the environment, or protect itself from the threats arising from the external environment.

3. Internal environment

(Culture, Structure, Products, Capabilities)
After external environment, the next element that business analysts must pay close attention to is the internal environment of the organization. Some the key factors that we look for in an internal environment are the culture of the organization, structure of the organization, the products that the organization has, services it provides, capabilities it has. If the internal environment becomes weak for an organization, it will also lead to the downfall of the organization. Organizations those do not develop capabilities continually or stop innovating or their culture becomes toxic, will for sure lead to organization’s failure.

4. Strategies

(Innovation, Cost leadership, Quality, Focus, Customer intimacy)
Based on the organizational vision, goal, objectives, understanding of the external and internal environments, the organization must develop suitable strategies to be successful in the marketplace. Common strategies that most organizations follow are innovation, cost, leadership, quality, focus, and customer intimacy. There can be multiple strategies playing together in the organization.
However, the organization must figure out what strategy works well for the given size and maturity of the organization and act accordingly. Strategy affects organizational operations as well as sets the direction for the organization. One must be very careful in choosing strategy but at the same time, not get paranoid regarding it. This is because the strategies may work or may not, and one must figure out and adjust the organization strategy as it moves forward in the organizational journey.

5. Customer management

(Segments, value propositions)
Though customers are stakeholders as well, we must differentiate them as they are the most valuable stakeholder in the organization. Customers are the only source of revenue for any organization and understanding customer needs is extremely vital for any organization to be successful. The organization should identify the different kinds of segments and then develop propositions of the right value, which will attract potential customers to the organization. At the same time, the organization also must understand profitability aspects for each of the customer segments and figure out a way to serve each customer segment profitably.

6. Cost management

(Structure, Optimization)
If costs are not managed well in an organization, it will lead to a drop in the profitability and finally leading to shutdown of the organization. As business analysts, we should understand the different elements of the cost structure, and which elements of the structure can be optimized for organizational benefit. At the same time, one must be careful that the lowest cost is not necessarily the optimized cost because the lowest cost could compromise on the product or service quality. This, in turn, would affect organization’s customer satisfaction and ability to earn revenue from its customers.

7. Stakeholder management

(Identification, Analysis, Engagement)
Business analysts need to understand stakeholders for the organization, initiative or project as everything that business analysts do must add value to the stakeholders. Effective stakeholder management is essential for the success of any change. Stakeholders could be internal or external to the organization.
Key steps that we would follow for stakeholder management would be to identify stakeholders, analyze stakeholders for the criticality and contribution. Of course, business analysts must engage with stakeholders to reap benefits from the initiative.

8. Product and services management

(Portfolio, Contribution, Improvement, Processes)
Next element that we business analysts need to understand is product and services of the organization. Most organizations offer multiple products and services. It is essential for the organizations to understand the portfolio that they would like to maintain, contributions coming from different product and service lines, what kind of improvements or innovations are possible in existing products and services, and to develop new products and services, and bring about improvements to the processes carried out in the organizations.

9. Risk management

(Identification, Analysis, Mitigation)
Any organization has multiple risks from different sources including external and internal sources. Organizations must be cognizant of the sources of risks that it faces and develop suitable mitigations for managing business risks. Some activities can put the organization at a serious loss (even leading to the closure of the organization). All of us know the story of Enron and Arthur Andersen when they violated government regulations and finally leading to the closure of both these organizations. Not understanding risks coming from technological or demographic changes of customers can lead to companies going bankrupt because their products no longer have demand in the marketplace.

10. Resource management

(People, Financial, Technological, Physical)
The last element we discuss is resource management. Resources are essential for delivering any product and services to customers. Different kinds of resources that the organization must develop, maintain, and improve include people resources, financial resources, technological resources, and physical resources.

Nature of resources that an organization should possess is changing dramatically over the time. For many services organization in the olden days, having physical assets was very helpful. Today, in certain segments, it’s probably better not to have physical assets, but rather have digital assets. Physical assets require a significant amount of money to be maintained. In future, organizations will develop more and more digital assets as maintaining digital assets cost less, and can earn revenue across the globe, whereas physical resources mostly earn revenue from a specific geography.