Business Intelligence Effectivity (Questions/Answers)

Is your Business Intelligence smart enough?

You may already be using Business Intelligence to improve what you do – but are you sure it’s as effective as it could be? Is your data accurate enough to effect real positive change in your operations? Can you react to events in your business’ activity in real-time?

In the everchanging landscape of business technology, Business Intelligence is still relatively new.

Business Intelligence is the collection and analysis of data collected such as department productivity, overall growth, sales trends, and customer behavior.

Reporting and querying software extracts, sorts, summarizes, and presents selected data. This data could range from sale reports of specific items to a measurement of the efficiency of marketing plans.

In a nutshell: Business Intelligence will help you manage your business more effectively.

However, as with any new technological initiative, it’s not quite that simple. There’s a key aspect of Business Intelligence that many organizations are failing to take into account.

What’s the biggest problem with Business Intelligence?

In a word?

Data quality.

As is the case with so many technologies (the cloud, security solutions, etc.), users often assume (or just hope) that it’s a matter of “set it and forget it”.

They’re either convinced by the marketing for the solution, or just plain aren’t interested in putting in the work to maximize the effect of their Business Intelligence efforts.

Without accurate data, Business Intelligence doesn’t end up being very intelligent, which can lead to a number of problems:

Unforeseen consequences
If an executive is relying on Business Intelligence to make key business decisions, but their data quality isn’t sufficient to actually allow them to make the right choices, then it would follow that they’ll make the wrong ones.

This will inevitably lead to wasted resources, whether it’s employees spending their time following a Business Intelligence-based process or workflow that doesn’t actually increase productivity, or lost funds invested in something that won’t pay off, or something else entirely.

Unidentified opportunities for improvement

When carried out correctly, Business Intelligence can help identify areas of an organization that can be improved. These could be efficiency bottlenecks, overspending, wasted employee minutes or hours, etc.

If an organization’s Business Intelligence is based on incorrect or incomplete data, then these sorts of problems may not be noticed and then left to contribute to further losses and effects to productivity.

It’s situations like these in which the need for high-quality data is so important. That being said, what does “high quality” data really mean?

Do you know if your data is high quality?

Quality of data can be affected by a range of factors, whether it’s a matter of how your database consolidates your business data, or conventional human error in tracking, collection, and reporting.

When evaluating your data, keep the following quality dimensions of data in mind to make sure that it’s of a high enough quality to be useful in Business Intelligence:

• Is it complete?

This is all about determining what is mandatory in data collection and what isn’t. If you don’t set the right parameters, then when it comes time to analyze and report, you may be left without everything you need.

For example, say you’re collecting data on the effectivity of marketing to a specific industry of potential clients – what if you were to fail to make their job title a mandatory part of the data you’re collecting on them?

While data such as their name, business, services or products purchased, and others may seem obvious, it’s a key bit of data like job title that may reveal more about how effective your marketing efforts are. That is, if you’re only getting in touch with receptionists (as opposed to managers and C-Level executives), shouldn’t that be reflected in your data?

• Is it in the right format?

This is a key consideration when it comes to using automated Business Intelligence software that is designed to crunch the numbers on large sets of data.

If your format for dates, for example, is inconsistent (mm/dd/yyyy vs. dd/mm/yyyy), your Business Intelligence software may not be able to reconcile the difference, leading to tedious, line by line analysis and correction on the part of one of your employees.

• Is it accurate?
  As with format, this is a vital aspect to double check prior to or during collection. A few examples of data accuracy questions you need to ask include:
  1. 1. Are names spelled correctly (and consistently correctly)?
     2. Do decimals fall in the correct positions, consistently across the same values?
     3. Is the data included in a report gleaned from the correct time frame? Or does it include all data collected, some of which is likely out of date?
• Is it consistent?
  Where and when the data collected should be identical, you need to make sure it is indeed identical.An example of where this could occur is between your marketing and sales efforts. As a new client is successfully transitioned from your marketing team to your sales team, it’s important to make sure all the data on that client matches across both systems.
• Does it have sufficient integrity?
  This is the last and, ultimately, the most important aspect of data collection for Business Intelligence purposes. When evaluating your data, you need to answer questions such as:
  1. 1. Is the data valid across all identified relationships?
     2. Is it possible to trace and connected data relationships where available?
     3. Are there duplications across systems (such as between marketing and sales, explored earlier) that cannot be linked?

As you can see, there’s a lot that goes into ensuring data quality is high enough to make your Business Intelligence efforts actually effective.
But don’t worry, there are options available to you to assist in these efforts – such as real-time metrics.

What do real-time metrics have to do with Business Intelligence?

Real-time Business Intelligence is the practice of not just gathering and reporting on data for organizational purposes, but doing so with information about processes as they occur.

What’s the point?

With real-time data, you automatically guarantee a number of the above dimensions for data quality. When it’s being gathered and analyzed in real time, there’s zero latency, which means the data is complete, up to date, and as accurate to your recent business activities as possible.

With the right solution, your business transactions can be fed into a real-time Business Intelligence system that maintains the current state of your enterprise, allowing you to identify and react to events as they occur, instead of waiting to review a report at regularly scheduled intervals.

For example, say your business has an online store – if an order is placed that cannot be fulfilled, you can be notified of that immediately, instead of through conventional, slower channels.

Ideally, given the speed of the latest real-time Business Intelligence solutions, this can be done so quickly that the customer can be referred to a similar item for purchase before they’ve left your site.

Real-time metrics are the gold standard of Business Intelligence – that’s why you need to find a solution that offers it, allowing you to make decisions with greater, more relevant insight.

A solution like Metridata.

What is Metridata?

Using industry-leading algorithms, analytics, and real-time metrics, Metridata equips you with the capability to detect patterns that help you to adjust your business for the future – otherwise known as business intelligence.

Metridata features include:

• Personalized coaching to plan and achieve a winning business intelligence program.
• Training for team members to effectively leverage data in their role.
• Development of reports, dashboards, and self-service analytics.
• Automated, secure and centralized company data assets.
• Ongoing support to keep things running smoothly.
• Special projects including data collection, analysis, and machine learning.

What does Metridata achieve?

• Increased Profits
  One of the most critical aspects of a business is profit – without it, everything stops. Business Intelligence aids your business’ profit by providing valuable insight into your activity and your customers’ behavior.Business Intelligence can increase your business’s profit, both current and future through the use of analytics and science-based predictors.
• Boosted Efficiency
  Efficiency is a vital cornerstone of any business. You can build the effectiveness of your small business operations in a few ways. Business intelligence analyzes data that comes from inside your organization as well as outside, such as those involving your customers and partners.

This analysis offers you an opportunity to see where gaps exist and where they don’t. It also looks for patterns of efficiency within your business by showing which departments are running efficiently, and which aren’t. These tools ensure that you and your staff are making efficient use of all your resources, no matter how large or small.

• Long-Term Strategy
  With accurate and up to date data available on all your business processes and initiatives, you can better plan for your future.You’ll know what works and how well it works, as well as what doesn’t, so you can adapt processes, invest more heavily in proven strategies, and more efficiently reach your business goals.

Long story short – stop stumbling around in the dark. Truly powerful Business Intelligence is about more than basic reporting. It’s about harnessing actionable intelligence to effect real change in your business for the better.

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