Don’t waste money on services that don’t work or people who try to change who you are. If you believe in your company’s mission, don’t let someone try to change, learn how to take your beliefs and turn them into a profitable reality. We would love to listen to your goals and help you find the best way to achieve them!
The key to saving money is to not spend it on the unnecessary. Well how do you decide what is necessary and not? This is sometimes a tricky tango that involves taking risks and investing in the resources you have.
Save money with more user friendly technology!
This means, don’t buy programs for your company that are so complex they require you to hire an entire IT team just to manage them. People love simple. Why is that? Because it is efficient, it allows us to spend more time on the important things rather than wrestling with the difficult.
One company that has grasped this concept is Salesforce. Some of you out there might be thinking whoa whoa wait a second, Salesforce, simple? Salesforce has just announced their launch of IoT Cloud which is a tool that workers can use to program unique actions based on Big Data. This tool takes Data from websites, social media, and internet devices and puts in in the hands of its user.
Not only does this tool make it much easier for a sales team to gain access to information, but it is also simple enough for a non “techy” person to use daily. The great part about this program is that any business that uses Salesforce can get an upgraded version without having to worry about if it is too complicated for their sales staff to use.
The best way to save money in a business is to invest in the people you already have, give them the tools needed to be successful and make things simple. Instead of spending money on an IT team, it is more beneficial to purchase an easy to use program and train your current staff to manage it.
To find out just how simple Big Data can make your life, CHECK OUT THIS VIDEO!
The saying “Time is Money” is one that has always been true whether you take it in the sense that life is short and therefore time is precious or more literally as in the amount of money you can make per hour. In regard to most businesses the saying is more about the second interpretation. What businesses should be asking is how can we make more money for our hour?
You cannot stretch time so the value that must be manipulated in money, and you make more money by being more productive. Therefore it all comes down to efficiency. Efficiency is something everyone strives for; being able to be more productive in a shorter amount of time.
The way to be more productive is to make whatever you are doing easier. This was the case for Pioneer West Virginia Credit Union who discovered their lack of efficiency in managing their 12,000 members. Before the use of Big Data Pioneer was receiving monthly status reports that were outdated and fragmented. Not only were the reports outdated but some poor employee was wasting hours on putting it together every month on a spreadsheet.
Pioneer also discovered they had excessive delinquency ratios on loans and were unsure how to fix it. Once Pioneer began using their Big Data as a tool they began receiving status reports daily and cut their loan delinquency from 150 basis points to 14 basis points. Not to mention that poor employee that was previously doing the reports manually, now has time to actually do his job.
This is a very small scale example of how Big Data can save money but it also shows that Big Data is not something just for the big boys, it is extremely useful for any business. No matter what you do, being more efficient leads to making more money. The best way to be more efficient is to use the tools and information available to make your job easier.
See how Big Data can make your job easier in this short video.
How dirty is your data? As business intelligence experts know, the answer to that question can have a tremendous impact on your organization’s efficiency. And although it may sound unsavory, the truth is that unreliable information, aka dirty data, is a common business intelligence problem for large companies.
Dirty data becomes a problem as businesses grow over time. As stores, offices, warehouses, and plants are established and enhanced, data systems multiply. Lack of standardization among these systems may allow users to produce inconsistent, invalid, or duplicated information, or simply fail to enter critical information.
While it may not have been a practical or intentional choice, lack of standardization allows for the adoption of different business rules and data systems across the company. Sites may use different sets of codes to represent similar products, services, or entities such as vendors, customers or lines of business. Data systems in use at some locations may collect information from users into free-form entry fields instead of using a “pick list” of options, increasing the likelihood of incorrect entries or multiple versions of a single value resulting from misspelling and typos. Furthermore, these systems may allow certain values such as names, addresses, or dates to be unexpectedly overwritten, limiting the ability to track historical events or create accurate business intelligence trend reporting.
When dirty data finds its way into reports, the results can be inaccurate and unusable, with important information distorted, excluded, or even multiplied many times over. When this happens, the hunt for meaningful, actionable business intelligence can become a laborious, never-ending quest.
Companies may not be aware of the full extent of their business intelligence problems, or may accept them as an unfortunate fact of life. Even if you know where the problems lie, you may have to follow elaborate and repetitive procedures to gather the business intelligence you need to succeed. Dirty data makes it difficult to consolidate and measure business results. Inaccurate and missing information prevents decision-makers from getting answers to their important questions about your business.
To evaluate the health of your data, consider the following business intelligence questions:
If your best analysts are spending the majority of their time compiling the data required to create reports, and the results always arrive at the last minute or past deadlines, it’s time to look into the role of business intelligence in your organization. Tackle the problem head-on with an experienced business intelligence expert who can identify and address dirty data issues, homogenize data across different systems and standards, and consolidate company-wide data so it is accessible and reportable whenever you need it. You’ll be on your way to creating a more strategic and action-oriented environment where those over-worked analysts can focus their efforts on analyzing results instead of preparing them.
To begin the process of addressing data quality, your business intelligence partner will need to understand your organization’s goals. Where do you want to be in five years? What has been keeping you awake at night? Identifying strategic priorities will help you outline a plan which focuses on the most relevant and critical information.
To establish high-quality, reliable data, the business intelligence team will filter, merge, standardize, and validate records, all with the end goal of simplifying life for the end user. But creating a great business intelligence solution involves much more than database management and coding. The process will likely involve identifying areas where company standards and business rules can be added or improved, and getting consensus from stakeholders to define the rules that will prevent future problems.
Working with the right business intelligence partner, you’ll ultimately find the treasure that every large business dreams of: a centralized, authoritative source of data, married to a business intelligence system that analyzes your business to pinpoint critical problems and highlight favorable opportunities, and then reports the results you need to measure progress and plan for the future.
Business Intelligence, Operational Efficiency and Dirty Data
by Paul Ousterhout, Business Support Expert
To learn more about business intelligence, visit www.cliintel.com or e-mail askcliintel@cliintel.com
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