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Top 7 Tips For Asking Business Intelligence Questions

man looking at a blackboard searching for the right business intelligence questions to ask

At the Big Data panel at the Strategic Competitive Intelligence Conference in Amsterdam, some years ago, one of the questions posed to the audience was a topic that every BI practitioner must address:  why do people focus more on the dataset rather than on the right business intelligence questions? In other words, when working with big data and business intelligence software, teams often find themselves focusing on the data, rather than the problems that the data can solve. One reason this can happen is because although organizing data is challenging, it may still be more straightforward than analyzing business problems.

As the book “Thinking, Fast and Slow” details, the human mind will often substitute an easier to answer question for a harder one. For example, instead of answering to “What are the insights from this data set?”, someone’s mind might answer instead: “how can I make sure this data is high quality?”. This isn’t to say that data quality management isn’t important, and that there aren’t challenges with bad data. But the real challenge comes from translating findings into actionable insights, applying them to business problems, and measuring the outcomes.

In this article, we’re going to go over 7 tips you can use to ask the right business intelligence questions. These tips will help link your BI efforts with benefits such as lower costs, more ROI on existing efforts, and new sources of revenue.

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1) Focus on Questions That Are Aligned With Your Business Strategy

The first step is to make sure that all team members implementing business intelligence are kept up-to-date on your company’s overall strategy and goals. The questions you ask, the data you gather, and the insights you glean should all be part of a larger plan.

As Myron Weber, founder of Northwood Advisors, a BI and decision systems advisory firm, states, “Establishing metrics and key performance indicators aligned with strategy, then using BI software to provide visibility and drive accountability, brings alignment of activities and outcomes with the desired strategic objectives”.

In order to have a team that is aligned and on the same page in terms of business intelligence, it helps to have a common set of objectives and a common vocabulary for describing those objectives. That’s where KPIs come in handy.

What are your KPIs?

marketing dashboard by datapine gathering main marketing KPIs

** click to enlarge **

We’ve written about KPIs in numerous places on this blog, but in a nutshell, KPIs are important metrics that reflect the underlying success or failure of key aspects of your business. It’s crucial to have KPIs established for each department and each position. It’s also essential to track these KPIs over time, so that you can see if your company is reaching its strategic goals or not.

It is also important not to have too many KPIs for any department or position - as the saying goes, “if you have too many priorities, you effectively have none.” These KPIs serve as a “North Star” your company can use to orient itself and give context to the success or failure of business decisions.

2) Ask BI Questions That Give You Actionable Insights

Asking very specific questions that lead to actionable insights is a great best practice to follow for effective business intelligence. You want your insights to be as nitty gritty as possible, so that your BI questions can translate into actions which have a tangible effect on your KPIs.

So, for example, instead of asking “How is our email marketing going?” you should instead ask something like, “How is our email marketing going this quarter according to the KPIs of email signups, click through rate, and revenue generated from email marketing compared to this quarter last year?”.

Notice that this question had:

  • A specific time frame mentioned
  • KPIs that were used to reflect reality
  • A comparison time frame for relative success

It could be a really useful one - for example, let’s say you are three months into a new email marketing strategy led by an outside marketing agency, and you’re trying to decide whether to renew their contract or not. With all of the specifics used in this example, you would be able to say whether you should continue to outsource your email marketing or take it back in house.

Here’s another example, using slightly different terms. Instead of asking, “How are sales this quarter?” you should instead ask, “How do sales this quarter compare to our projections according to the KPIs of gross revenue, revenue per customer, and new customers?”. Notice a theme here?

Questions that lead to actionable insights incorporate the use of KPIs, the use of a specific time period, and the use of contrast to other metrics (like a previous time period or projections) to give detailed and useful answers.

Time Frames Matter

Man working on his macbook with a clock included as watermark to symbolize time

One important note: you need to use an appropriate time frame of comparison in order to get realistic insights.

To make the point, here’s an exaggerated example: you start a new content marketing strategy, and then two weeks later, you ask, “How is this new content marketing strategy working compared the old one over these past two weeks using the KPIs of new email signups, average time spent on site, and backlinks generated?”.

This is an amazing question with the wrong timeframe. Realistically, content marketing takes much longer than 2 weeks to see effects… heck, it could take 2 quarters to see measurable results. However, if you’re doing B2C sales, then you could see changes in sales within a week or two of enacting a new strategy. Context is crucial.

One good question leads to another...

If you use a great question that leads to a clear answer, you now have the opportunity to gather more well defined business intelligence through further questions. For example, if you concluded that outsourcing your email marketing was working well, you could then ask, “What factors are leading to this strategy working well?” While harder to answer than the first, it can lead to very powerful insights.

We go more into this thread later in the article when we examine using “why” questions.

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3) Questions that Identify Opportunities for ROI

One of the most popular topics for business intelligence and big data analysis is ROI.  A study shows that organizations can expect an average ROI of $13.01 for every dollar they spend on BI, up from an average ROI of $10.66 in 2011. The study surveyed companies of various sizes and industries using different BI solutions.

Instead of asking something broad like “How can I increase ROI?”, drill down and be specific. Perhaps your churn rate is higher than you would like it to be. If so, ask what separates your engaged users from the users who drop off, then analyze your entire data history to discover why some customers leave and how to keep them.

Keep your questions specific and related to opportunities where you can apply the insights to boost profits.

4) Questions That Identify Opportunities For New Sources of Revenue

Asking questions that lead to new revenue streams can be a really valuable tactic to show senior management how much ROI you are getting from the time and money spent on BI. After all, when it comes to the C-suite, the stereotype of “revenue above all else” often holds true.

William Duncan, Corporate Director of IOT & Business Technology at Emerson, gives some examples you can use for revenue generation in his LinkedIn post, “Asking the Right Questions to Make Big Data and Business Intelligence Pay Off”.

Here are a few:

  • “What opportunities exist for my products and services to be used differently, so that my market can be expanded?
  • What other products and services are sold to similar customers that I might be able to use as cross-selling platforms, to enlarge my sales?
  • What are my customers planning to do in the months and years ahead that I could enable with my products / services, thereby increasing my sales?”

5) Questions Identifying Cost-cutting Opportunities

Man in suit working on a desk with a lot of papersheets and post its

Data analysis software can often pay for itself by providing insights that enable your team to identify cost-saving opportunities.

Some of the best case studies on using BI to cut costs have occurred in retail and fashion. Business intelligence has alerted companies to cut excessive inventory and streamline their supply chains.

The example of fashion is a good one as it can be a tricky industry when trying to predict success. With the latest generation of tools, shops can aggregate trends and combine them with past sales information, and social media/fashion blogs, to more accurately predict the inventory they will need for the upcoming season. A well-designed KPI dashboard enables retailers to understand the data at a glance.

6) Questions That Begin With “Why”

“How” questions are much easier to answer confidently than “why” questions. Earlier  we outlined how to effectively ask “how” questions - as in, how is this specific area of our business going according to certain KPIs, time frames, and/or projections?

These types of questions lead to only a few answers: things are going well, badly, or they are neutral. And while they are useful, they aren’t quite as powerful as “why. “Why" is much tougher to answer than "how", but it can be much more powerful because it can show you the underlying causes of success and/or failure in your business.

For example, knowing that your sales are up this quarter is useful. But knowing WHY those sales are up is much more useful, because then you can focus on the causes leading to your current sales growth.

However, it’s important to be aware that whenever you are answering a “why” question, you are going to have to make assumptions. Modern businesses are complex, dynamic systems with lots of moving parts, and so you have to be aware that you’re likely to be wrong a lot of the time when answering “why". At the very least, your BI related to causes will likely be incomplete.

Cutting through contradictions and confusion

“Why” can also be very useful in areas where there is a seeming contradiction between different KPIs. For example, let’s say your company’s revenue  this quarter is up, and revenue per customer is up, but the number of new customers this quarter is down. Why is that happening?

There are a number of possible reasons, including but not limited to:

  • Your client relations team is performing very well, but your sales team is underperforming.
  • Your new marketing strategy does a bad job of accurately describing your product or service’s value - once customers experience your solution, they’re hooked. But the new marketing strategy makes it harder to sell them in the first place.
  • There’s been a bad turn in the economy that has led to a sales drought, but your service is so excellent that you are deepening relationships with existing customers and they are spending more.

Any of these reasons could be possible, or none of them. It’s hard to know for sure. That’s one of the challenges of business - you rarely have certainty with “whys", but you can have reasonable best guesses which you are constantly testing.

From here, you can ask additional questions with your data to “test” these hypotheses. For example, with the first assumption of client relations doing well, but sales doing poorly, you would ask, “Is this hypothesis true?” and examine KPIs like:

  • Your churn rates this quarter compared to last
  • Your sales closing rates this quarter compared to last
  • How many leads per week your sales team is in contact with
  • The customer satisfaction ratings your team is getting

7) How Can You Understand Your Customers Better?

One of the most valuable questions you can ask is: how can we engage our customers better? Start with your definition of ‘engagement’. Once you have a baseline, use your BI tools to discover patterns in your customer behavior, which could help you make more sales, develop new features, or increase customer participation, all of which will directly lead to greater profit.

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Try a 14-days free trial & uncover the hidden potential behind your data!

Data is a resource, but it’s only valuable if it is used correctly. The right BI questions are the best way to utilize data for the greatest benefit.  Here’s a summary:

  1. Ask important questions
  2. Ask specific questions that lead to actionable insights
  3. Ask questions that have have built-in potential for ROI
  4. Ask questions that will lead to new revenue streams
  5. Ask questions that will identify cost-cutting opportunities
  6. Ask questions that will help you understand “why”
  7. As questions that will help you understand your customers better

When the right business intelligence questions are combined with the right tools, profits will follow.