Month: June 2020

Process improvement involves the business practice of identifying, analyzing and improving existing business processes to optimize performance, meet best practice standards or simply improve quality and the user experience for customers and end-users.

Process improvement can have several different names such as business process management (BPM), business process improvement (BPI), business process re-engineering, continual improvement process (CIP), to name a few. Regardless of the nomenclature, they all pursue the same goal: to minimize errors, reduce waste, improve productivity and streamline efficiency.

1. Six Sigma

Six Sigma is a methodology that uses data and statistics to improve process efficiency and reduce variations. It initially began at Motorola, was then adopted by General Electric, and thereafter began to be widely used for manufacturing and business processes. There are two sub-methodologies within Six Sigma–DMAIC (Define, Measure, Analyse, Improve, Control) and DMADV (Define, Measure, Analyse, Design, Verify)–which are used for existing and new processes respectively.

2. Lean Thinking

Lean thinking involves doing away with any activity that doesn’t bring value to the process. It was started at Toyota and is still a very effective methodology today. It is often used in combination with the Six Sigma method.

The difference between Six Sigma and Lean Thinking is that while Six Sigma eliminates defects for quality assurance, Lean Thinking eliminates all wasteful practices in order to achieve efficiency.

This method includes examining the value stream of a process to differentiate value-added activities (that result in customers paying for the product or service) from non-value added activities (that complete a concept or an order). If something doesn’t add value or form part of policy and regulation, it is considered wasteful. Process engineers map out the steps to deliver a product or service with the help of a value stream map.

3. Total Quality Management (TQM)

Here, customer satisfaction is the end goal and the yardstick by which success is measured. The US federal government began using this method in the 1980s after which it began gaining widespread attention.

These are the principles that govern the TQM method.

• Customers determine the level of quality
• All employees work toward common goals
• Focus on process thinking
• Focus on processes that connect vertical functions
• A strategic and systematic approach
• Continual process improvement
• Data-based decision making
• Effective communication with employees

4. Kaizen

The Kaizen methodology was initially implemented in Japanese companies after WWII. A Japanese term, Kaizen means ‘to take apart’ and ‘to make good’. This methodology focuses on making small incremental changes that are routinely applied over a sustained period to improve performance. Kaizen attempts to improve productivity and eliminate wasteful activities in processes.

5. PDCA

PDCA is an acronym for Plan-Do-Check-Act. This methodology is based on the notion of continuous improvement to carry out change. This model is carried out repetitively. It involves coming up with a proposed plan, testing out the plan, measuring its effectiveness, and implementing feedback.

6. Whys

This method was developed and utilized by Toyota as part of problem-solving training. The goal is to conduct a root cause analysis in a problem. As the name suggests, you ask “why” five times until you eventually uncover the actual problem that needs to be fixed. This analysis can be conducted using a fishbone diagram or tabular columns.

7. Cause and Effect analysis

Another tool born from Six Sigma is Cause and Effect analysis, which involves using a diagraming method to fix problems the first time by identifying the problem, discovering road blocks and pinpointing why the process isn’t working.

8. SIPOC analysis

As a diagram format that falls under the Six Sigma methodology, SIPOC analysis happens during the “measure” stage of DMAIC or DMADV. SIPOC helps organizations define and establish a process improvement project as well as identify requirements and necessary elements before starting.

9. Value stream mapping (VSM)

VSM helps organizations visually represent customer’s perceptions of a business process, which helps identify the value of a product, process or service to the organization. Similar to other methodologies, it’s highly focused on eliminating waste, redundancy and being as lean as possible.

10. Process mapping

Another workflow visualization that helps companies map out a plan for process improvement is process mapping. It can also be called a process flowchart, process chart, functional flowchart and process model. Ultimately, it’s the process of creating a flow diagram that delivers vital information about a process workflow from start to finish.

Automation’s role in process improvement

Because it’s one of the easiest ways to improve processes is to eliminate manual toil and reduce human error, automation plays a significant role in process improvement. Process automation helps organizations understand where they need to improve and what is working as it should.

Robotic process automation (RPA) is a hot topic in automation and businesses have embraced the practice to streamline processes. It allows organizations to mimic human actions for tasks or steps involved in complex processes. Automation occurs through a string of rules and triggers that eliminate the need for manual labor in specific parts of the process and allow the RPA to do what a human previously had to do.

Some process improvements that are automated with RPA includes automated email responses, online order processing, categorizing help desk tickets, transferring data between systems and payroll management. This not only helps create more efficiency around business process, but it also helps free up workers to focus on more complex tasks that automation can’t handle.

Picking the Best Business Process Improvement Methodology

Although there are multiple effective BPM methodologies, the right one should suit your business requirements and resolve any issues you may be facing. It should help enhance process efficiency and minimize errors.

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Diffusion is the process by which an innovation is communicated through certain channels, over time, among the members of a social system. It is a special type of communication concerned with the spread of messages that are perceived as new ideas and which will necessarily be received with some degree of uncertainty. The four main elements in the diffusion of new ideas are:

• Innovation
• Communication channels
• Time
• The social system

1. The Innovation

An innovation is an idea, practice, or object that is perceived as new. The characteristics of an innovation, as perceived by members of a social system, determine its rate of adoption. Some innovations diffuse relatively slowly, while other innovations diffuse rapidly. The characteristics that determine an innovation’s rate of adoption are its relative advantage, compatibility, complexity, trialability, and observability.

The relative advantage of an innovation reflects the degree to which it is perceived as better than the idea it supercedes. The degree of relative advantage may be measured in economic terms, but social prestige, convenience, and satisfaction are also important factors. It does not matter so much if an innovation has a great deal of objective advantage. What does matter is whether individuals perceive the innovation as advantageous. The greater the perceived relative advantage of an innovation, the more rapid its rate of adoption will be.

Compatibility is the degree to which an innovation is perceived as being consistent with the existing values, past experiences, and needs of potential uses. An idea that is incompatible with the values and norms of a social system will not be adopted as rapidly as an innovation that is compatible. The adoption of an incompatible innovation often requires the prior adoption of a new value system, which is a relatively slow process. Technological compatibility may be involved in cases where a particular software program cannot be used because it will not work with a computer’s operation system.

Complexity refers to the degree to which an innovation is perceived as difficult to understand and use. Some innovations are readily understood by most members of a social system; others are more complicated and will be adopted more slowly. New ideas that are simpler to understand are adopted more rapidly than innovations that require people to develop new skills and understandings.

Trialability is the degree to which an innovation may be experimented with on a limited basis. New ideas that can be tried on an installment plan will generally be adopted more quickly than innovations that are not divisible. An innovation that is trialable represents less uncertainty to the individual considering using it and who can learn by doing.

Observability is the degree to which the results of an innovation are visible. The easier it is for individuals to see the results of an innovation, the more likely they are to adopt it. Such visibility stimulates peer discussion of a new idea, as friends and neighbors of a user of a product often request information about it.

Overall, innovations that are perceived by individuals as having greater relative advantage, compatibility, trialability, and observability, and as less complex, will be adopted more rapidly than other innovations.

2. Communication Channels

The second main element in the diffusion of new ideas is the communication channel. Communication is the process by which participants create and share information with one another to reach a mutual understanding. A communication channel is the means by which messages get from one individual to another. Mass media channels are more effective in creating knowledge of innovations, whereas interpersonal channels are more effective in forming and changing attitudes toward a new idea, and thus in influencing the decision to adopt or reject a new idea.

Most individuals evaluate an innovation, not on the basis of scientific research by experts, but through the subjective evaluations of peers who have adopted the innovation. So the diffusion process is essentially social in nature, driven by individuals talking to others and giving meaning to an innovation through a process of social construction.

3. Time

The third element in the diffusion of new ideas is time. The time dimension is involved in three ways.

First, time is involved in the innovation-decision process. This is the mental process through which an individual (or other decision-making unit) passes from first knowledge of an innovation to forming an attitude toward the innovation; then to a decision to adopt or reject it; then to implementation of the new idea; and finally to confirmation of the decision to adopt the innovation. An individual seeks information at various stages in the innovation-decision process in order to decrease uncertainty about an innovation’s expected consequences.

The second way in which time is involved in diffusion is in the innovativeness of an individual or other unit of adoption. Innovativeness is the degree to which an individual or other unit of adoption is relatively earlier in adopting the new ideas than other members of a social system. There are five adopter categories, or classifications of the members of a social system on the basis of their innovativeness. These categories are: (1) innovators, (2) early adopters, (3) early majority, (4) late majority, and (5) laggards.

Innovators are defined as the first 2.5 percent of the individuals in a system to adopt an innovation. Venturesomeness is almost an obsession with innovators. This interest in new ideas leads them out of a local circle of peer networks and into more cosmopolitan social relationships. Control of substantial financial resources is helpful to absorb possible losses from an unprofitable innovation. The ability to understand and apply complex technical knowledge is also needed. The innovator must be able to cope with a high degree of uncertainty about an innovation at the time of adoption. While an innovator may not always be respected by the other members of a social system, the innovator plays an important role in the diffusion process.

Early adopters are the next 13.5 percent of the individuals in a system to adopt an innovation. Early adopters are a more integrated part of a social system than are innovators. Whereas innovators are cosmopolites, early adopters are localites. This adopter category, more than any other, has the greatest degree of opinion leadership in most systems. Potential adopters look to early adopters for advice and information about an innovation. Early adopters are the embodiment of the successful use of new ideas, and they know that to continue to earn the esteem of colleagues and to maintain a central position as an opinion leader they must make judicious innovation decisions.

The early majority category contains the next 34 percent of individuals in a system to adopt an innovation. The early majority adopt new ideas just before the average member of a system. They interact frequently with their peers, but seldom hold positions of opinion leadership in a system. The early majority’s unique position between the very early and the relatively late to adopt makes them an important link in the diffusion process.

The late majority is the next 34 percent of the individuals in a system to adopt an innovation. The late majority adopt new ideas just after the average member of a system. Like the early majority, the late majority make up one-third of the members of a system. Adoption may be the result of increasing network pressures from peers. Innovations are approached with a skeptical and cautious air, and the late majority do not adopt until most others in their system have done so. The weight of system norms must definitely favor an innovation before the late majority are convinced. The pressure of peers is necessary to motivate adoption.

Laggards are the last 16 percent of the individuals in a system to adopt an innovation. They possess almost no opinion leadership. Laggards are the most local in their outlook of all adopter categories; many are near isolates in the social networks of their system.

The third dimension in which time is involved in diffusion is in rate of adoption. This is the relative speed with which an innovation is adopted by members of a social system. The rate of adoption is usually measured as the number of members of the system that adopt the innovation in a given time period.

4. The Social System

The fourth main element in the diffusion of new ideas is the social system. A social system is defined as a set of interrelated units that are engaged in joint problem solving to accomplish common goals. The members or units of a social system may be individuals, informal groups, organizations, and/or subsystems. The social system constitutes a boundary within which an innovation diffuses. Diffusion is affected by norms, which are the established behavior patterns for the members of a social system, and by opinion leadership, which is the degree to which an individual is able to influence the attitudes or overt behavior of other individuals in a desired way with relative frequency.

A key concept in understanding the nature of the diffusion process is the critical mass, which occurs at the point at which enough individuals have adopted an innovation so that the innovation’s further rate of adoption becomes self-sustaining. The concept of the critical mass implies that outreach activities should be concentrated on getting the use of the innovation to the point of critical mass. These efforts should be focused on the early adopters, who are often opinion leaders and serve as role models for many other members of the social system. Early adopters are instrumental in getting an innovation to the point of critical mass, and, therefore, they are instrumental in the successful diffusion and adoption of an innovation.

Technology is an essential need in everyone’s life. It gets a bad rap sometimes, but without it we never would have put a man on the moon, we’d still be taking our horse and buggy to work every day and we’d actually have to “like” our friends in real life. Technology makes life easier and more enjoyable, no matter what your lifestyle or career.

We recently returned from the “real-world meets big data” conference of the year, Trimble Dimensions, where innovation was in the spotlight. Although the conference focused on how technology is evolving the construction industry, there are many parallels that can be drawn to any industry. Here are the key takeaways from the conference.

Impact 1: Adopting Innovation Saves Time and Money

Some may argue that the initial investment for new technology is a waste of money. The way we work is ultimately changing, and adapting to that reality could save big bucks in the long run.

At Trimble Dimensions, it was obvious that the way construction operators control and maneuver their equipment must change. Technologies like Cat® Connect GRADE and PAYLOAD assist operators in knowing how they’re manipulating the earth or materials around them. This specificity increases operator accuracy and technique, saving them money and time down the road. Also, monitoring machine health lowers operating costs and extends machine life.

Today you have to do more with less to stay competitive, and adapting to innovation will only help.

Impact 2: New Solutions Increase Workplace Safety

Unless you work in the automotive industry or in healthcare, you probably don’t give much thought to workplace safety. As the need for security and safety heightens, we are finding better ways than ever to use technology. Security in schools is getting better, new measures are put in place for the safety of airline pilots and cyber-security continues to increase.

The construction industry isn’t immune either. Trimble Dimensions highlighted how advancements in technology are keeping operators safe with enhancements like Driver Safety System and Fatigue Risk Management.

Impact 3: Technology Improves Cross Communication

This is a big one, because communication touches every facet of business for every industry. The better the communication, the more efficient the project, the more money and time saved and on and on.

For the construction industry, operators in one machine need to work in conjunction with other operators and machines. The impact of technology-equipped machines creates clear lines of communication. Offerings like Cat Connect Equipment Management Services helps owners understand their machines and moves business forward.

There are plenty of innovative platforms, technologies and gadgets to choose from now. And our options will continue to grow. We feel this as a company, too. We now have remote team members working in five different states, so facilitating online collaboration is key for us.

Impact 4: The Right Platform Helps to Optimize Return

At the forefront of the conference was how to transform data into easy-to-use information, something that is necessary in any industry. It’s difficult to do, but harnessing the power of data is required in today’s data heavy environment.

The main objective for the construction industry is to optimize return on the equipment and the workforce. But how do business owners set a benchmark and know what parts of the operation need optimization? That’s where Product Link comes in. Product Link tracks information about the location, utilization and condition of equipment.

No matter the industry, make sure to do your due diligence on the right platforms and technologies to use. And most importantly, allocate time and money to be able to make changes based on the data collected. That’s the main point of data, right?

What is innovation and why do we need it?

Innovation, by definition, is the introduction of something new. Without innovation, there isn’t anything new, and without anything new, there will be no progress. If an organization isn’t making any progress, it simply cannot stay relevant in the competitive market.

Because organizations are often working with other individual organizations, it can sometimes be challenging to understand the impacts of innovation on our society at large. There is, however, a lot more to innovation than just firms looking to achieve competitive advantage.

Innovation really is the core reason for modern existence. Although innovation can have some undesirable consequences, change is inevitable and in most cases, innovation creates positive change.

The diffusion of innovation is the process by which new products are adopted (or not) by their intended audiences. It allows designers and marketers to examine why it is that some inferior products are successful when some superior products are not.

The idea of diffusion is not new; in fact it was originally examined by Gabriel Tarde, a French sociologist, in the 19th century. However, it wasn’t until the 1920s and 1930s that the phenomenon began to be investigated in depth by researchers.

One of the most significant early studies was conducted by Ryan and Gross in 1943. This solidified previous research into the adoption of seeds in agricultural communities and provided a strong basis for diffusion research in the future.

In his book, Diffusion of Innovations published in 1962, Everett Rogers, a sociology professor, provides a full framework for diffusion of innovation based on over 500 studies into the phenomenon in many different disciplines. Rogers’ text, to this day, provides the formal understanding on which modern research into the diffusion of innovation is based.

The Process for Diffusion of Innovation

Rogers’ draws on Ryan and Gross’s work to deliver a 5 stage process for the diffusion of innovation.

1. Knowledge

The first step in the diffusion of innovation is knowledge. This is the point at which the would-be adopter is first exposed to the innovation itself. They do not have enough information to make a decision to purchase on and have not yet been sufficiently inspired to find out more.

At this stage marketers will be looking to increase awareness of the product and provide enough education that the prospective adopter moves to the 2nd stage.

As it was once said (by whom we’re not sure); “If the user can’t find it, it doesn’t exist.”

2. Persuasion

Persuasion is the point at which the prospective adopter is open to the idea of purchase. They are actively seeking information which will inform their eventual decision.

This is the point at which marketers will be seeking to convey the benefits of the product in detail. There will be a conscious effort to sell the product to someone at this stage of the diffusion of innovation.

3. Decision

Eventually the would-be adopter must make a decision. They will weigh up the pros and cons of adoption and either accept the innovation or reject it.

It is worth noting that this is the most opaque part of the process. Rogers cites this as the most difficult phase on which to acquire intelligence. This is, at least in part, due to the fact that people do not make rational decisions in many instances. They make a decision based on their underlying perceptions and feelings and following the decision they attempt to rationalize that decision. Thus, obtaining an understanding of the decision making process is challenging the reasons given following a decision are not likely to be representative of the actual reasons that a decision was made.

4. Implementation

Once a decision to adopt a product has been made the product will, in most cases, be used by the purchaser. This stage is when the adopter makes a decision as to whether or not the product is actually useful to them. They may also seek out further information to either support the use of the product or to better understand the product in context.

This phase is interesting because it suggests that designers and marketers alike need to consider the ownership process in detail. How can a user obtain useful information in the post-sale environment? The quality of the implementation experience is going to be determined, to a lesser or greater extent, by the ease of access to information and the quality of that information.

5. Confirmation

This is the point at which the user evaluates their decision and decides whether they will keep using the product or abandon use of the product. This phase can only be ended by abandonment of a product otherwise it is continual. (For example, you may buy a new car today you are highly likely to keep using the car for a number of years – eventually, however, you will probably sell the car and buy a new one).

This phase will normally involve a personal examination of the product and also a social one (the user will seek confirmation from their peers, colleagues, friends, etc.)

Diffusion and Adoption

It is worth noting that adoption is the process by which a user begins and continues to use a product; diffusion is a measure of the rate of adoption. It considers the relationship not just between any given user and a product but the relationship between all users, each other and the product.

Rogers’ diffusion studies offered some interesting advice for driving the rate of diffusion including:

Examining social networks (it’s worth noting that Rogers wasn’t talking about Facebook or LinkedIn here though the idea applies in a similar way in digital networks but rather “real life” social networks) and finding highly respected individuals and working with them to create desire for an innovation

• Determining a representative group of desired users and “injecting” the innovation into that group to gain positive feedback, case studies, etc. to help make the decision making process easier for other would-be early adopters
• Diffusion recognizes that adoption is not an isolated process but rather one which is influenced heavily by other members of the adoption cycle.

Failure of Diffusion

Failure for a product to diffuse within a market does not always mean that there is a flaw in the product. It may mean that the product has failed due to competition from other innovations or simply because of a lack of awareness or knowledge.

Rogers cites a village called Las Molinas in Peru. This place of poverty had high rates of disease. Villagers did not understand the relationship between cleanliness and their own health.

This should have been easy to address; the residents had the resources to devote to hygiene and thus just required education. A campaign team arrived to provide that help. They taught how to boil water for drinking, to burn garbage to prevent it from contaminating healthy materials, and how to install and use toilets.

Simple enough, right? So was the campaign a success? No. The educational efforts were confused by the local people. Their impression was, for example, that boiled water was only something that sick people needed. Thus a social stigma developed regarding the consumption of boiled water if you were healthy.

Diffusion of innovations is a theory that seeks to explain how, why, and at what rate new ideas and technology spread. Everett Rogers, a professor of communication studies, popularized the theory in his book Diffusion of Innovations; the book was first published in 1962, and is now in its fifth edition (2003). Rogers argues that diffusion is the process by which an innovation is communicated over time among the participants in a social system. The origins of the diffusion of innovations theory are varied and span multiple disciplines.

Rogers proposes that four main elements influence the spread of a new idea: the innovation itself, communication channels, time, and a social system. This process relies heavily on human capital. The innovation must be widely adopted in order to self-sustain. Within the rate of adoption, there is a point at which an innovation reaches critical mass.

The categories of adopters are innovators, early adopters, early majority, late majority, and laggards. Diffusion manifests itself in different ways and is highly subject to the type of adopters and innovation-decision process. The criterion for the adopter categorization is innovativeness, defined as the degree to which an individual adopts a new idea.

The concept of diffusion was first studied by the French sociologist Gabriel Tarde in late 19th century and by German and Austrian anthropologists and geographers such as Friedrich Ratzel and Leo Frobenius. The study of diffusion of innovations took off in the subfield of rural sociology in the midwestern United States in the 1920s and 1930s. Agriculture technology was advancing rapidly, and researchers started to examine how independent farmers were adopting hybrid seeds, equipment, and techniques. A study of the adoption of hybrid corn seed in Iowa by Ryan and Gross (1943) solidified the prior work on diffusion into a distinct paradigm that would be cited consistently in the future. Since its start in rural sociology, Diffusion of Innovations has been applied to numerous contexts, including medical sociology, communications, marketing, development studies, health promotion, organizational studies, knowledge management, conservation biology and complexity studies, with a particularly large impact on the use of medicines, medical techniques, and health communications. In organizational studies, its basic epidemiological or internal-influence form was formulated by H. Earl Pemberton, such as postage stamps and standardized school ethics codes.

In 1962, Everett Rogers, a professor of rural sociology, published his seminal work: Diffusion of Innovations. Rogers synthesized research from over 508 diffusion studies across the fields that initially influenced the theory: anthropology, early sociology, rural sociology, education, industrial sociology and medical sociology. Using his synthesis, Rogers produced a theory of the adoption of innovations among individuals and organizations. Diffusion of Innovations and Rogers’ later books are among the most often cited in diffusion research. His methodologies are closely followed in recent diffusion research, even as the field has expanded into, and been influenced by, other methodological disciplines such as social network analysis and communication.

Characteristics of innovations

Studies have explored many characteristics of innovations. Meta-reviews have identified several characteristics that are common among most studies. These are in line with the characteristics that Rogers initially cited in his reviews.

Potential adopters evaluate an innovation on its relative advantage (the perceived efficiencies gained by the innovation relative to current tools or procedures), its compatibility with the pre-existing system, its complexity or difficulty to learn, its trialability or testability, its potential for reinvention (using the tool for initially unintended purposes), and its observed effects. These qualities interact and are judged as a whole. For example, an innovation might be extremely complex, reducing its likelihood to be adopted and diffused, but it might be very compatible with a large advantage relative to current tools. Even with this high learning curve, potential adopters might adopt the innovation anyway.

Studies also identify other characteristics of innovations, but these are not as common as the ones that Rogers lists above. The fuzziness of the boundaries of the innovation can impact its adoption. Specifically, innovations with a small core and large periphery are easier to adopt. Innovations that are less risky are easier to adopt as the potential loss from failed integration is lower. Innovations that are disruptive to routine tasks, even when they bring a large relative advantage, might not be adopted because of added instability. Likewise, innovations that make tasks easier are likely to be adopted. Closely related to relative complexity, knowledge requirements are the ability barrier to use presented by the difficulty to use the innovation. Even when there are high knowledge requirements, support from prior adopters or other sources can increase the chances for adoption.

Characteristics of individual adopters

Like innovations, adopters have been determined to have traits that affect their likelihood to adopt an innovation. A bevy of individual personality traits have been explored for their impacts on adoption, but with little agreement. Ability and motivation, which vary on situation unlike personality traits, have a large impact on a potential adopter’s likelihood to adopt an innovation. Unsurprisingly, potential adopters who are motivated to adopt an innovation are likely to make the adjustments needed to adopt it. Motivation can be impacted by the meaning that an innovation holds; innovations can have symbolic value that encourage (or discourage) adoption. First proposed by Ryan and Gross (1943), the overall connectedness of a potential adopter to the broad community represented by a city. Potential adopters who frequent metropolitan areas are more likely to adopt an innovation. Finally, potential adopters who have the power or agency to create change, particularly in organizations, are more likely to adopt an innovation than someone with less power over his choices.

Characteristics of organizations

Organizations face more complex adoption possibilities because organizations are both the aggregate of its individuals and its own system with a set of procedures and norms. Three organizational characteristics match well with the individual characteristics above: tension for change (motivation and ability), innovation-system fit (compatibility), and assessment of implications (observability). Organizations can feel pressured by a tension for change. If the organization’s situation is untenable, it will be motivated to adopt an innovation to change its fortunes. This tension often plays out among its individual members. Innovations that match the organization’s pre-existing system require fewer coincidental changes and are easy to assess and more likely to be adopted. The wider environment of the organization, often an industry, community, or economy, exerts pressures on the organization, too. Where an innovation is diffusing through the organization’s environment for any reason, the organization is more likely to adopt it. Innovations that are intentionally spread, including by political mandate or directive, are also likely to diffuse quickly.

Product Specification

A product specification (also referred to as “product specs”) is a document with a set of requirements that provides product teams the information they need to build out new features or functionality.

A product specification is a strategic document with requirements aimed to provide product teams with the data they need to develop new product features. It is also known as Product Specs.

An effective product specification gives team members relevant context about business needs, potential customers/ users, and other useful criteria that help them make right decisions as they design solutions.

Product managers will agree that a well-written specification should contain clarity and transparency.  The more information you add to your spec, the more clarity you’ll give the team working on the product.

A good product spec doesn’t micro-manage product development. Rather, it gives them relevant context about users, business needs and other criteria to help them make informed decisions as they design and build a solution.

What goes into a product specification?

Product specs don’t have be long or overly technical. In fact, the most effective product specs are actually pretty brief.

You know your product spec has done its job when it answers the following questions:

• What are we building and why?
• What should the final build achieve?
• How do we measure success?

How to write a product specification?

• Define the sources of problems.
• Use customers’ feedback.
• Determine and evaluate requirements.
• Break a specific problem down into hypotheses.
• Add the pages/screens with all the features if needed.
• Arrange discussions across your team if needed.
• Add user testing with your closest customers.
• Simplify the document.
• Send the spec to development.

Establishment of Specifications

1. Start with the Problem

The best way to build products your customers will buy is to get out there and talk to your target market long before you start writing your specification. First, you need to articulate your problem statement.

A product problem statement is a few sentences or paragraphs that describe a market need. They are written from the perspective of the persona that has the problem and—this is critical—say nothing about how to actually solve the problem. The goal of this stage in the exploration is to convey an understanding of the problem and a sense of the value associated with solving it.

A problem statement generally is made up of three parts:

• The first is the persona, or a description of who has the problem. It is helpful to describe the persona in great detail separately and then reference a particular persona in the problem statement to keep from repeating the same persona description.
• Next is a description of the problem. The more detail the better here. You want to make sure that the need is crystal clear. Also, give the problem a name. This makes it easier for teams to refer back to it during the project.
• Finally, write a description of how often the problem occurs. If the problem happens rarely and has low impact, then solving it is of low value. If the problem happens frequently and has high impact, then the value of solving it will be high.

You can start by asking customers what problems they have that they think you can solve, but you have to dig deeper to get to the truly valuable problem statements or golden nuggets. These golden nuggets generally come from developing a deep understanding of the market and piecing together information from a wide range of sources.

If you do this successfully, you’ll end up identifying a problem that you can solve and that your customer will pay for.

During the process, be careful that you don’t run into false positives or negatives. Listening too much to people inside your company or only a small number of customers can lead you to falsely validate or abandon a problem. Talk to as many customers as you can and collect as much data as possible.

2. From problem statement to specification

Now that you have your problem statements and the team has become familiar with them, start collaboratively developing a product specification. Since everyone on the team understands the problem being solved, everyone can contribute to the specification.

Because you’ve done the upfront work of identifying the problem you’re solving, within identified constraints, and your team has considered multiple ways to deliver the solution, you have enough information to write the product spec.

3. Release the Product Specification in Small Batches

The best approach here is to release small pieces of the specification to the team as early as possible to get fast feedback.  This will help avoid wasting time going down the wrong path and will make it much easier for the team to provide high-quality feedback.

Not convinced? Consider this: What happens if you receive a 200-page spec sheet to review? You probably look at the first few pages and then skim the rest.

Now, what happens if you receive a one-page document? You probably review the whole thing. Two-hundred one-page documents will result in much better feedback than a single 200-page document.

4. Refer to the Problem Statement to Ensure You’re on Track

Also, as you develop the specification, check back to make sure that the product is still a valid solution to the problem. It is easy to get caught up in the trade-off inherent in developing a product and forget to check and see if you are still on target.

This approach also manages the expectations of your stakeholders. As the process is controlled, there is a framework and transparency that prevents anyone from overriding decisions. At any point in the project, you’ll be able to explain exactly what value your product offers and why it needs to have the features that the team has specified.

The target specifications are established after the customer needs have been identified but before the product concepts have been generated and most promising one(s) selected.

The process of establishing the target specification contains four steps:

1. Prepare the list of metrics.
2. Collect competitive benchmarking information.
3. Set ideal and marginally acceptable target values.
4. Reflect on the results and the process.

Step 1: Prepare the list of metrics

A simple needs-metrics matrix represents the relationship between needs and metrics. The row of matrix corresponds to the customer needs, and the columns of the matrix correspond to the metrics. A mark in a cell of the matrix means that the metric associated with the cell is related.

Step 2: Collect competitive benchmarking information

A competitive benchmarking chart will help to give information on competing products and thereby takes positioning decisions. The columns if this chart corresponds to the competitive product and the rows are the metrics established in step 1.For each competitive product, the values of the metrics are simply entered down a column.

Step 3: Set ideal and marginally target values.

In this step, the team synthesizes the available information in order to actually set the target values for the metrics. Two types of target values are useful: an ideal values and a marginally acceptable value. The ideal value is the best result the team could hope for.

The marginally acceptable value is the value of the metric that would just barely make the product commercially visible.

There are five ways to express the value of the metrics.

• At least X
• At most X
• Between X and Y
• Exactly X
• A set of discrete values

Step 4: Reflect on the result and the process

Reflection after each iteration helps to ensure that the result are consistent with the goals of the project. Once the targets have been set, the team can proceed to generate solution concepts. The target specifications then can be used to help the team select a concept and will help the team know when a concept is commercially viable.

No matter what you do for a living, the success of your business probably depends on how good and creative you are. The ability to come up with fresh and exciting ideas is what separates top-performers from their less successful peers, so you definitely need to think of how to improve this skill.

Idea generation is defined as the process of creating, developing and communicating abstract, concrete, or visual concepts. To put it simply, it’s the process that requires finding new solutions for practical problems in all fields of life and work.

But how can you improve idea generation? Is there a way or tactic to strengthen your problem-solving capacity? The simple answer is: Yes, there is. As a matter of fact, there are many different techniques you can try, so keep reading to discover seven creative idea generation methods.

1. The 5W+H Method

Although it may seem like a random set of numbers at first glance, the 5W+H method is a really meaningful way to cope with the creative drought. The technique represents basic questions you need to ask when thinking about a specific topic: Who, what, where, when, why, and how?

Jason Richardson, a content creator at essay papers, shared his thoughts with us: “If you answer each of the 5W+H questions precisely regardless of the topic you can get one step closer to solving your problem. These answers should stimulate your brain to rethink the whole subject and find a new angle of looking at things.”

2. Social Listening

Idea generation doesn’t mean you have to come up with a great suggestion single-handedly. On the contrary, sometimes it’s enough to do a little bit of social listening and see what the target audience has to say about a certain topic. You can use social networks like Facebook or Twitter to find precious ideas coming from end-users.

Besides that, you can always organize an opinion poll to directly ask people what they want. For example, a platform such as Survey Monkey allows you to launch a simple survey within minutes, so why not use it as the idea generation tool?

3. Brainstorming

Brainstorming is a well-known method that people all over the world use for decades already. What makes this tactic so popular? Well, it’s the fact that no one gets laughed at for proposing a stupid idea. There is no right or wrong here – you just need to say the first thing that comes to your mind and that’s it. After a quick brainstorming session, you just need to filter through all suggestions and find the ones that have the biggest potential to succeed.

4. Role Playing

Walking in someone else’s shoes is everything but easy, but sometimes it’s the only way to break the barrier and think of a brilliant idea. The process is simple: you just need to switch places with your colleagues and try to embrace their point of view. It doesn’t guarantee immediate results, but it often leads to interesting conclusions and brand new ideas.

5. Use Online Tools

The Internet is filled with interesting tools that can assist you in identifying alternative ideas. You can choose between many different options, but the final decision usually depends on the nature and peculiarities of your business. However, we can definitely recommend a couple of valuable platforms here:

Evernote: Nothing hurts like coming up with amazing solutions and forgetting it along the way. Evernote prevents this because it allows you to write down every thought instantly.

Ninja Essays: It’s a team of incredibly creative authors who can help you to brainstorm and craft high-quality topics for your websites, blogs, or research papers.

6. Mind Mapping

Mind mapping is another method to get through the creative drought successfully. By definition, a mind map is a diagram for representing tasks, words, concepts, or items linked to and arranged around a central concept or subject using a non-linear graphical layout that allows the user to build an intuitive framework around a central concept.

Let’s say you are writing a screenplay. In this case, you can put the main character in the center of the map and then add links leading to all other elements of your movie from plot and love relationships to supporting roles.

7. Think In Reverse

The last solution on our list is very amusing. Instead of thinking about how to reach your goal, you can think about how not to achieve it. For example, you can make a plan on how to reduce the number of Instagram followers instead of increasing it. The so-called negative thinking often leads people to unbelievable conclusions, which in turn brings them a bunch of new ideas.

Conclusion

You can be the most creative person in the world, but it won’t save you from an occasional creative drought. Everybody knows that feeling when you feel miserable because you just can’t seem to think of a good idea, but there is a way to get out of the whole.