3 Assets You Need for a Better Business By Miranda Marquit

rawpixel / Pixabay

As you work on your startup and, later, grow your business, it’s important to consider your assets and how they can help you reach success.

If you’re trying to figure out which assets you need to achieve success with your fledgling venture, there are three to keep in mind:

1. People

Much of the time, we neglect to think about human capital when starting a business. However, the people you have on your side matter. The people you hire, outsource to, and turn to should all be high quality.

And it’s not just about the people you pay, either. Your people-related assets also include potential business partners and mentors. Build your network in a way that allows you to connect with people who can provide you with inspiration, ideas, and encouragement.

The people you surround yourself with can make a huge difference in your long-term success. No matter what you’re trying to accomplish, the right people are among the assets you need to reach your business goals.

Be careful about who you select, and make sure you treat them fairly, whether you’re paying them or whether you’re maintaining long-term networks. Nurture talent, acknowledge help, and show gratitude. And make sure you help others succeed — just as you want them to help you succeed.

2. Financial

It would be nice if you could just manage your startup without the need for financial assets. However, if you want to be successful in the long run, you need to come up with monetary assets that can be used to invest back into your venture.

Sometimes, getting the assets you need requires that you borrow, or look into venture capital. Other times, you can get the financial assets you need as you go. This is common with freelancers. A small investment in a computer and the internet can help you start earning money. Later, you can take the money you earn and use it to set up an office or hire a virtual assistant.

No matter how you approach the situation, though, it’s important to understand that your financial assets need to be used wisely. Whether you get a loan or whether you find someone willing to back you, it’s vital to understand where the money will do the most good — especially if you’re just starting out and operating on a shoestring.

3. Audience

Finally, don’t forget that your audience is one of the assets you need to move forward. Without someone to buy your products or services, you won’t get very far.

You need to connect with those who can benefit from your product or service, providing them with something that meets their needs.

Your audience isn’t just your current customers or clients, though. Your potential customers and clients are also important assets you need if you expect to grow over time. Provide them with an experience that validates them while offering something they can use, and you might be surprised at how well you can develop a loyal following.

When you focus on these three assets in your business, you are likely to come out ahead, no matter the situation.

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How Competency Models Can Address Your Business Needs By Darleen DeRosa

Free-Photos / Pixabay

Leadership can make or break an organization. Despite the enduring myth of the “born” leader, in most cases effective leadership is the result of a carefully crafted development process. In order to achieve sustained business success, companies must find ways to identify and promote vital skills and behaviors in their employees that will bring about consistent and measurable results.

A well-designed competency model is one of the most effective tools for establishing what characteristics an effective leader should possess. While they’re primarily used to guide hiring, promotion, and performance evaluations, competency models also provide a number of additional advantages. Here are a few ways these models can benefit an organization.

Consistency and Clear Expectations

Employees like to know what an organization expects of them. This is especially true of millennials, who are accustomed to receiving feedback regarding their performance and want to have a clear idea of how to advance their careers. A good competency model serves both roles by establishing very specific skills and behaviors necessary for success within an organization.

For this very reason, it’s often beneficial for employees to take part in the process of creating these models. By providing feedback throughout the model’s development, employees can provide a different perspective on what leadership skills are most effective and necessary. Being involved in the process also makes them more likely to buy into and use the model in the future.

A well-designed competency model has the advantage of being fair and reasonably objective. Employees know what criteria they must meet and the skills they must acquire if they want to advance their careers. This allows them to take ownership over their own development, which can be both empowering and reassuring.

Cultivate Leadership Strategies

If an organization is experiencing high turnover, frequent employee-related complaints, or poor business performance, it’s worth reevaluating their leadership competency models. In many cases, these problems can be traced back to leaders who aren’t prepared for their positions or lack the skills necessary to be successful. While it may be tempting to place the blame on a few “bad hires,” the reality is that most of these people were put in a position to fail by a flawed hiring or promotion process.

Organizations can take the first steps to resolving this problem by emphasizing what outputs they want get from their leaders. At their core, competency models must reflect the company’s overall strategic goals. When they do not align, leaders will struggle to find success.

Focusing too heavily on technical competencies, for instance, can produce leadership candidates who know how to perform a variety of specialized tasks, but lack the soft skills necessary to manage their teams effectively. There is a tendency to take these skills for granted, but ignoring them in the early stages of development can leave candidates woefully unprepared for leadership positions later in their careers.

A good leadership competency model should be aligned with the organization’s goals to continuously develop leaders who help to drive its mission forward. By identifying what successful leaders have done to achieve strategic results, they can develop a model of observable and measurable behaviors that can be integrated into existing systems for hiring, promoting, and evaluating candidates. While getting the right competency model in place isn’t a “cure-all” for a struggling company, it can go a long way toward identifying the reasons behind existing problems and laying the groundwork for developing long-term solutions.

Reframe Expectations

The process by which organizations hire and promote employees can have a tremendous impact on performance and culture. When business circumstances change, companies need to find ways to adapt with them in order to survive. But this process is rarely easy and institutional changes take time to implement. Employees become can become set in their ways, especially if they’re accustomed to working under a different set of expectations.

Establishing new competency models is an effective first step in reframing what an organization expects from its employees. Strategic changes often require employees to develop a different set of strengths and skills. Competency models provide guidance for the types of characteristics and behaviors needed for future success in leadership positions.

For example, when Pep Boys made the decision to shift to a more customer service-oriented company, one of the most important steps it took was to implement a new set of competencies that reinforced the cultural change. Rather than basing hiring and promotion primarily on mechanical skill, the company emphasized the development of social skills like communication and conflict resolution. By changing the expectations for employees and leadership, Pep Boys made a commitment to lasting change that would better position it for success in a dynamic industry.

Better Succession Planning

One of the major challenges facing organizations today is developing the next generation of leaders. Surprisingly, over 70% of executives don’t believe their leaders are ready to lead their companies into the future. As baby boomers in leadership positions age out of the workforce, the need for solid succession planning is more important than ever.

Since competency models play a major role in identifying and developing future leaders, it’s imperative that organizations establish the appropriate criteria for these candidates. A well-designed competency model that’s in keeping with an organization’s goals and values can save both time and money by helping to select and develop high-potential employees more effectively.

It’s important to keep in mind, however, that a competency model isn’t a foolproof method for producing the “perfect” leaders. Too much emphasis on creating a checklist of what makes a good leader can diminish diversity within an organization and inadvertently select for qualities that might not contribute to leadership success. Competencies should also not be treated as endpoints. They are skills and behaviors leaders need to develop on an ongoing basis rather than benchmarks to be met in order to qualify for a promotion.

With a strong leadership competency model in place, organizations can make sure they’re directing the appropriate candidates into the right positions and getting the most out of them after they’re in place. While starting out with the ideal competencies is a challenge in itself, the ever-changing demands of today’s economy require companies to revise these models periodically to make sure they’re still in line with their culture and goals. As a new generation of leaders move into positions with greater responsibilities, establishing good leadership competency models is more important than ever.

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Work Smarter, Not Harder… Today By Personal Branding Blog

geralt / Pixabay

That old saying of Work Smarter Not Harder is very easy to say.

However, it’s much hard to do.

To Stand Out in Your Career it will take focus, practice, and foresight.

In order to start Working Smarter and Not Harder… Today. You’ll need to brace yourself, prepare yourself, and hold yourself accountable for both successes and failures. Part of working harder includes embracing the successes and learning from the failures.

Let’s dig into it a little.

Work smarter. – What does it mean?

Work harder – what does that mean?

By themselves and with no context they are effectively meaningless.

But, this is where you come in and apply your business sense your logic.

In the real world we don’t always get to decide what we work on. We also don’t always get to decide when we work on things. Deadlines, customer commitments, life commitments, and lots of other things have a way of getting in the way. This is where the focus comes in. It’s also where your voice comes in. Hint: You need to get comfortable saying no.

Even if you don’t get to decide what you work on, and to some extent, when you work on something it is still up to you to decide when and how you will work on it.

Putting Work Harder Not Smarter to Work

Set the goal… not the steps to get there.

U.S. Army General George S Patton was famous for providing the goal but not providing how to get there.

Just as in the military where campaign success and results matter more than the methodology used to get there the same is true for business and in life. Learning how to decipher where to spend your time as well as deciding WHAT get’s your focus is a task that can be daunting and fraught with challenges. Fortunately, there are a few tips and tricks to help you evaluate where you get the most value for your time. And, ultimately, time is your most precious asset. Once it’s gone, it’s gone.

Using The Four Quadrants do Decide

The four quadrants are a tried and true methodology that can help you decide what to focus on, what to drop, and what to prioritize. Again, you don’t always get to decide every factor here. But, oftentimes you do have a lot more control that you might think. Stephen Covey summarized the four quadrants quite nicely in his time management grid. See the table on page 2 of this USGS training document.

There is a table that shows four quadrants of importance. Quadrants I and II are where you should be spending your time. Quadrants III and IV are areas you should seek to avoid or at least minimize.

There are books and courses available that go into depth on the time management grid. I’ll save that as an exercise for you, the reader.

Putting it all Together

When you learn to use The Four Quadrants and Learn to Say No Like a Pro you’ll be well on your way to Working Smarter and Not Harder … Today!

via Technology & Innovation Articles on Business 2 Community http://bit.ly/2me0wvN

Work Smarter, Not Harder… Today By Personal Branding Blog

geralt / Pixabay

That old saying of Work Smarter Not Harder is very easy to say.

However, it’s much hard to do.

To Stand Out in Your Career it will take focus, practice, and foresight.

In order to start Working Smarter and Not Harder… Today. You’ll need to brace yourself, prepare yourself, and hold yourself accountable for both successes and failures. Part of working harder includes embracing the successes and learning from the failures.

Let’s dig into it a little.

Work smarter. – What does it mean?

Work harder – what does that mean?

By themselves and with no context they are effectively meaningless.

But, this is where you come in and apply your business sense your logic.

In the real world we don’t always get to decide what we work on. We also don’t always get to decide when we work on things. Deadlines, customer commitments, life commitments, and lots of other things have a way of getting in the way. This is where the focus comes in. It’s also where your voice comes in. Hint: You need to get comfortable saying no.

Even if you don’t get to decide what you work on, and to some extent, when you work on something it is still up to you to decide when and how you will work on it.

Putting Work Harder Not Smarter to Work

Set the goal… not the steps to get there.

U.S. Army General George S Patton was famous for providing the goal but not providing how to get there.

Just as in the military where campaign success and results matter more than the methodology used to get there the same is true for business and in life. Learning how to decipher where to spend your time as well as deciding WHAT get’s your focus is a task that can be daunting and fraught with challenges. Fortunately, there are a few tips and tricks to help you evaluate where you get the most value for your time. And, ultimately, time is your most precious asset. Once it’s gone, it’s gone.

Using The Four Quadrants do Decide

The four quadrants are a tried and true methodology that can help you decide what to focus on, what to drop, and what to prioritize. Again, you don’t always get to decide every factor here. But, oftentimes you do have a lot more control that you might think. Stephen Covey summarized the four quadrants quite nicely in his time management grid. See the table on page 2 of this USGS training document.

There is a table that shows four quadrants of importance. Quadrants I and II are where you should be spending your time. Quadrants III and IV are areas you should seek to avoid or at least minimize.

There are books and courses available that go into depth on the time management grid. I’ll save that as an exercise for you, the reader.

Putting it all Together

When you learn to use The Four Quadrants and Learn to Say No Like a Pro you’ll be well on your way to Working Smarter and Not Harder … Today!

via Technology & Innovation Articles on Business 2 Community http://bit.ly/2me0wvN

The Continuum of Data-Driven Success By Annette Franz

Image courtesy of Pixabay


Data is just data until you do something with it, right?!

That statement has plagued companies for a long time. For a variety of reasons, not the least of which is that they just don’t know what to do with the data.

In December 2017, I hosted a webinar with Logi Analytics titled 5 Steps to Making Data Actionable, in which I shared tips on moving beyond data for the sake of data – and dashboards for the sake of dashboards – to recommending insights and outputs that drive action, I thought I’d share some details about one of the areas I covered during my presentation: how data-driven decisions and actions have evolved, particularly for customer experience professionals.

Customer experience professionals know that, in order to deliver a great experience, companies must listen to customers, link customer feedback to transactional (and other) data, and act on what they hear. There’s an old Gartner statistic that I still like to share because I believe it’s relevant to this day:

95% of companies collect customer feedback, yet only 10% use the feedback to improve, and only 5% tell customers what they are doing in response to what they heard.

This statistic is a good, high-level representation of how companies have matured or evolved (or haven’t) along the continuum of data-driven success.

Let’s take a closer look at that continuum. And let’s assume that Phase 0 is not listening or looking at data at all.

Phase 1 (Feedback) is where we see companies in the primitive stages of understanding the importance of data, i.e., they know they need to listen to their customers, oftentimes because everyone else is doing it. But that’s all they do; they check the box to say, “We listen.” And they’re paralyzed by the reams of data that exist within their systems.

In Phase 2 (Metrics), companies pick up their next bad habit when it comes to customer listening and understanding: they focus on a metric, on making their number, on moving the needle on the score. Doing that, instead of using data to improve the customer experience, is not really progress, and it’s not really a good thing. When you focus on the metric, you reward the behaviors that move the number, not on those that deliver a better experience. those (former, not latter) behaviors are often bad behaviors.

The next level in the data-driven success continuum is Phase 3 (Insights). Now we’re starting to make some progress. Companies at this level are interpreting the data, digging for insights, and telling the story of the data. They are making some data-driven improvements, mainly tactical at this point.

In Phase 4 (Outcomes), companies realize they cannot just make improvements without linking the findings and the work to be done to operational metrics and business outcomes. They realize they’ll make greater progress and get the resources (human, capital, and more) if they can show that “if we do X, it will impact Y.”

And finally, in Phase 5 (Innovation), we see some real progress! Companies us the data, the insights, and the linkages to make some real, significant, strategic improvements: they use the data to develop new products that solve problems for customers and help them do some job, and they redesign the customer experience to better meet customers’ expectations.

The important component along each phase is, obviously, the data and what is done with the data. Critical to that is the way the data is presented to the one who consumes it and needs to do something with it. There’s definitely an evolution in analysis and reporting, as well, as companies mature along the continuum. The output goes from basic descriptive statistics to metrics and trends to insights and stories to ROI and financial linkages to predictive and prescriptive recommendations that retain customers.

Consider these things when you’re developing reports and dashboards for customer experience professionals or for those who need to consume customer data in order to improve the experience. The data needs to be presented in a way that’s actionable; more specifically, it needs to tell the user exactly what needs to be done, why, and what the impact of making the change will be.

There are two goals when presenting data: convey your story and establish credibility. -Edward Tufte

via Technology & Innovation Articles on Business 2 Community http://bit.ly/2NOFlgE

The Continuum of Data-Driven Success By Annette Franz

Image courtesy of Pixabay


Data is just data until you do something with it, right?!

That statement has plagued companies for a long time. For a variety of reasons, not the least of which is that they just don’t know what to do with the data.

In December 2017, I hosted a webinar with Logi Analytics titled 5 Steps to Making Data Actionable, in which I shared tips on moving beyond data for the sake of data – and dashboards for the sake of dashboards – to recommending insights and outputs that drive action, I thought I’d share some details about one of the areas I covered during my presentation: how data-driven decisions and actions have evolved, particularly for customer experience professionals.

Customer experience professionals know that, in order to deliver a great experience, companies must listen to customers, link customer feedback to transactional (and other) data, and act on what they hear. There’s an old Gartner statistic that I still like to share because I believe it’s relevant to this day:

95% of companies collect customer feedback, yet only 10% use the feedback to improve, and only 5% tell customers what they are doing in response to what they heard.

This statistic is a good, high-level representation of how companies have matured or evolved (or haven’t) along the continuum of data-driven success.

Let’s take a closer look at that continuum. And let’s assume that Phase 0 is not listening or looking at data at all.

Phase 1 (Feedback) is where we see companies in the primitive stages of understanding the importance of data, i.e., they know they need to listen to their customers, oftentimes because everyone else is doing it. But that’s all they do; they check the box to say, “We listen.” And they’re paralyzed by the reams of data that exist within their systems.

In Phase 2 (Metrics), companies pick up their next bad habit when it comes to customer listening and understanding: they focus on a metric, on making their number, on moving the needle on the score. Doing that, instead of using data to improve the customer experience, is not really progress, and it’s not really a good thing. When you focus on the metric, you reward the behaviors that move the number, not on those that deliver a better experience. those (former, not latter) behaviors are often bad behaviors.

The next level in the data-driven success continuum is Phase 3 (Insights). Now we’re starting to make some progress. Companies at this level are interpreting the data, digging for insights, and telling the story of the data. They are making some data-driven improvements, mainly tactical at this point.

In Phase 4 (Outcomes), companies realize they cannot just make improvements without linking the findings and the work to be done to operational metrics and business outcomes. They realize they’ll make greater progress and get the resources (human, capital, and more) if they can show that “if we do X, it will impact Y.”

And finally, in Phase 5 (Innovation), we see some real progress! Companies us the data, the insights, and the linkages to make some real, significant, strategic improvements: they use the data to develop new products that solve problems for customers and help them do some job, and they redesign the customer experience to better meet customers’ expectations.

The important component along each phase is, obviously, the data and what is done with the data. Critical to that is the way the data is presented to the one who consumes it and needs to do something with it. There’s definitely an evolution in analysis and reporting, as well, as companies mature along the continuum. The output goes from basic descriptive statistics to metrics and trends to insights and stories to ROI and financial linkages to predictive and prescriptive recommendations that retain customers.

Consider these things when you’re developing reports and dashboards for customer experience professionals or for those who need to consume customer data in order to improve the experience. The data needs to be presented in a way that’s actionable; more specifically, it needs to tell the user exactly what needs to be done, why, and what the impact of making the change will be.

There are two goals when presenting data: convey your story and establish credibility. -Edward Tufte

via Technology & Innovation Articles on Business 2 Community http://bit.ly/2NOFlgE

6 Types of Overprovisioned Resources Wasting Money on Your Cloud Bill By Elaina Arce

Nikin / Pixabay

In our ongoing discussion on cloud waste, we recently talked about orphaned resources eating away at your cloud budget, but there’s another type of resource that’s costing you money needlessly and this one is hidden in plain sight – overprovisioned resources. When you looked at your initial budget and made your selection of cloud services, you probably had some idea of what resources you needed and in what sizes. Now that you’re well into your usage, have you taken the time to look at those metrics and analyze whether or not you’ve overprovisioned?

One of the easiest ways to waste money is by paying for more than you need and not realizing it. Here are 6 types of overprovisioned resources that contribute to cloud waste.

Unattached/Underutilized Volumes

As a rule of thumb, it’s a good idea to delete volumes that are not attached to instances or VMs. Take the example of AWS EBS volumes unattached to EC2 instances – if you’re not using them, then all they’re doing is needlessly accruing charges on your monthly bill. And even if your volume is attached to an instance, it’s billed separately, so you should also make a practice of deleting volumes you no longer need (after you backup the data, of course).

Underutilized database warehouses

Data warehouses like Amazon Redshift, Google Cloud Datastore, and Microsoft Azure SQL Data Warehouse were designed as a simple and cost-effective way to analyze data using standard SQL and your existing Business Intelligence (BI) tools. But to get the most cost savings benefits, you’ll want to identify any clusters that appear to be underutilized and rightsize them to lower costs on your monthly bill.

To identify a cluster as “underutilized,” you can set criteria based on CPU percentage and ReadIOPs/WriteIOPs follow the criteria below for Amazon Redshift clusters and use with other providers accordingly.

Underutilized relational databases

Relational databases such as Amazon RDS, Azure SQL, and Google Cloud SQL offer the ability to directly run and manage a relational database without managing the infrastructure that the database is running on, or a having to worry about patching of the database software itself.

As a best practice, Amazon recommends that you check the configuration of your RDS for any idle DB instances. You should consider a DB instance idle if it has not had a connection for a prolonged period of time, and proceed by deleting the instance to avoid unnecessary charges. If you need to keep storage for data on the instance, there are other cost-effective alternatives to deleting altogether, like taking snapshots. But remember – manual snapshots are retained, taking up storage and costing you money until you delete them.

Underutilized Instances/VMs

We often preach about idle instances and how they waste money, but sizing your instances incorrectly is just as detrimental to your monthly bill. It’s easy to overspend on large instances or VMs that are you don’t need. With any cloud service, whether it’s AWS, Azure, or GCP, you should always “rightsize” your instances and VMs by picking the instance size that is optimized for the size of your workload – be it compute optimized, memory optimized, GPU optimized, or storage optimized.

Once your instance has been running for some time, you’ll have a better idea of whether not the chosen size is optimal. Review your usage and make cost estimates with AWS Management Console, Amazon CloudWatch, and AWS Trusted Advisor if you’re using AWS. Azure users can review their metrics from Azure Monitor data, and Google users can import GCP metrics data for GCP virtual machines. Use this information to find under-utilized resources that can be resized to better optimize costs

Inefficient Containerization

Application containerization allows multiple applications to be distributed across a single host operating system without requiring their own VM, which can lead to significant cost savings. It’s possible that developers will launch multiple containers and fail to terminate them when they are no longer required, wasting money. Due to the number of containers being launched compared to VMs, it will not take long for container-related cloud waste to match that of VM-related cloud waste.

The problem with controlling cloud spend using cloud management software is that many solutions fail to identify unused containers because the solutions are host-centric rather than role-centric.

Idle hosted caching tools (Redis)

Hosted caching tools like Amazon ElastiCache offer high performance, scalable, and cost-effective caching. ElastiCache also supports Redis, an open source (BSD licensed), in-memory data structure store, used as a database, cache and message broker. While caching tools are highly useful and can save money, it’s important to identify idle cluster nodes and delete them from your account to avoid accruing charges on your monthly bill. Be cognizant of average CPU utilization and get into the practice of deleting the node if your average utilization is under designated minimum criteria that you set.

How to Combat Overprovisioned Resources (and lower your cloud costs)

Now that you have a good idea of ways you could be overprovisioning your cloud resources and needlessly running up your cloud bill – what can you do about it? The end-all-be-all answer is “be vigilant.” The only way to be sure that your resources are cost-optimal is with constant monitoring of your resources and usage metrics. Luckily, optimization tools can help you identify and automate some of these best practices and do a lot of the work for you, saving time and money.

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