If business people still base 40% of their major decisions on gut feeling, isn’t that a bit like gambling? With big money riding on a decision, why is it so hard for business and IT leaders to make decisions based on BI and the numbers? Is it because some data may be missing, or that we don’t have one version of the truth? Why exactly does the gut win out over the head and BI?

Contributors

• • Stuart Kippelman, Vice President and Chief Information Officer, Covanta Energy
  • Tony Bender, Executive Vice President, Chief Information Officer and Chief Technology Officer, McKesson Corporation

Transcript (Gut Feel vs. BI)

Speaker A [00:00:01]:
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Speaker B [00:00:33]:
Welcome to CIO Talk Radio with your host, Sanjog Aul. All comments, views and opinions expressed on this show are strictly those of the host, guests and callers. Here’s Sanjog Aul.

Sanjog Aul [00:00:48]:
Good morning and welcome to CIO Talk Radio. To learn more about the show, please visit www.ciotalkradio.com and also join our online community and exchange your ideas. Today’s topic is Gut Feel vs. BI and our guests for Today show are Tony Bender, who’s the Vice President and CIO with Alberta Culver. Morning, Tony.

Tony Bender [00:01:11]:
Good morning, Sanjog.

Sanjog Aul [00:01:13]:
How are you, sir?

Tony Bender [00:01:15]:
I’m great. Wonderful. Sunny day in Chicago.

Sanjog Aul [00:01:19]:
I know. Once few and far between type of days, right?

Tony Bender [00:01:23]:
Exactly.

Sanjog Aul [00:01:25]:
Thank you so much. It was great having you here.

Tony Bender [00:01:28]:
Thank you for the invitation.

Sanjog Aul [00:01:31]:
Thank you so much again. Now we also have Stuart Kippelman, who’s the Vice President and CIO with Coventa Energy. How are you, Stuart?

Stuart Kippelman [00:01:38]:
I’m very good. Thank you for the invitation as well.

Sanjog Aul [00:01:42]:
We’re going to have a ball, trust me. This is because the topic that we picked up today is about decision making and guess when you were not making decisions when you were in a CIO hot seat and then the goal here is to try to figure out that is there a balance or this decision making is always going to remain an art or it’s going to convert into a science given the cool tools that we have available today as bi. So let’s start with you, Tony. When we talk about IT decisions we make small and big, both type of decisions. What level of due diligence is truly performed at a formal level and when do you define or you can in a way decide whether you should have a due diligence behind a decision being made?

Tony Bender [00:02:33]:
Yes, Sanjog, these are decisions that the business is making or that it is making around investment decisions.

Sanjog Aul [00:02:42]:
Because when we use the word BI, it is not truly a decision being made by it alone. The business is using BI to make a decision. But yes, there would be some business decisions being made versus IT decisions being made.

Tony Bender [00:02:56]:
Yeah and I think, you know, as I look at this, is that, you know, we’re serving the business and our business, you know, associates, our counterparts in the business, are having to make decisions every day, you know, hundreds of decisions that they’re looking at making and they’re relying heavily on the information that we’re providing them through business intelligence and other analytic mechanisms and so I think to a large degree is that, you know, in order to make better informed decisions, they’re saying, well, what data do I have, what information do I gather from that data and then how do I establish insights so that I can act upon that data? And so I think to me it’s all about business intelligence providing the ability to get insight and so that we can act upon it because otherwise there is no real value to the business. So I think many of the executives in the company are making experiential knowledge that they’re making decisions off of but I think depending on the size of the prize, going back to your question of due diligence, of how much needs to be performed, is that if you’re looking at a decision that has, you know, if the size of the prize of the decision is very large, then obviously you need to do more due diligence but and then the quality of the information that they’re getting through BI or advanced analytics. So I think to a large degree is that it’s going to be a continuum of, you know, if it’s a fairly low cost, low risk scenario, then you can be very, you know, a gut feeling sort of decision making. The higher up the curve of expenditure and cost and risk to the company, obviously the more due diligence needs to be made.

Sanjog Aul [00:04:58]:
So Stuart, in your view, when you have looked at people making decisions, whether for business or for it, when they say that I am performing due diligence, do they really have a defined approach to doing that due diligence or you know what, let’s check everything, whatever is possible and then make a decision. Is there a process, is there a formal process of due diligence behind every decision at least, which is worth something?

Stuart Kippelman [00:05:28]:
You know, I’ll support everything that was just said as well. I think it depends on the size of the company. I think it depends on not just the size of the decision, but the impact of the business of the decision. So there are obviously many small decisions that can have a very significant impact on the company’s well being so, you know, I think that’s going to vary. BI is one of the many tools that it has and one of the many tools that it brings to the table from a value creation perspective and also depending on the decision will depend on how big of a percentage of that decision is given to the BI capability. So in my experience I’ve seen both sides where business intelligence is actually used to automate decisions on one end. The other side I’ve seen it where it is just one of the inputs into that overall gut experience of an executive that needs to make a decision.

Stuart Kippelman [00:06:42]:
They use BI as another level of input in that decision making process.

Sanjog Aul [00:06:50]:
Now how does it, how important does it becomes to when they look at the business looks at it to say you are going to provide me BI so I’m sure you will do whatever best it is. How much do they trust what you produce?

Stuart Kippelman [00:07:05]:
You know, it just depends on the company and the executive. I think as time progresses and it is moving from and has been moving from more of a back office function to more value creation. Even in many companies probably that are listening to the point of generating revenue from IT or technology capabilities, I think that trust is being earned more and more but it is a trust, it’s not something that’s given for free and it’s responsibility to make sure that the solution being delivered obviously is what the business is looking for. You’re answering the right, the appropriate questions that the business is asking and that the sources of data are of quality. So it’s the usual. It could be the old model of garbage in, garbage out, where if you’re using BI on top of old systems and that you have not verified the data or the data is inaccurate, you’re not going to get good quality results and the quality of the data and it doing due diligence of the data is critical to make sure that the answer is accurate.

Sanjog Aul [00:08:36]:
So Tony, in your view suppose it is asked to shepherd the data and the data quality and cleansing. We really realistically feel that it is first of all our responsibility and secondly, even if you are given that responsibility, are we successfully able to do it because the origination of data happens at many of those places where the business is in control?

Tony Bender [00:09:02]:
Yeah, actually it’s a very good point and one that’s really germane to us here at Alberta because we just went through a large SAP implementation recently and we had discussions around master data integrity of not just what’s in the system but what is the sustaining mechanism for it. And we put into place a central data management group that actually rolls up into our supply chain organization. But we were for a series of a few months I was taking responsibility with an IT for that data and I’d have to say that IT can play that role in terms of governing IT as far as auditing the data, ensuring data quality standards. The reality though is that much of that data in terms of ownership goes back to business transactions and those business transactions, there has to be ownership within the business to really, to really ensure that data is correct and some of it has very profound effects for new product launches, for supply chain management, etc. So I don’t think it’s wise to have that function managed under IT,

Tony Bender [00:10:23]:
I do think that there should be clear business ownership. IT certainly can assist the business in providing data hygiene and cleansing technologies to help ensure that we have efficient ways of auditing the data.

Sanjog Aul [00:10:40]:
Now, with that being said, does business really care when you are providing BI that they should go and first clean the data for you to get any tools? Because if they’re looking up to you, they’re looking up to you for a full solution?Tony?

Tony Bender [00:10:55]:
Well, it’s a very to that point. I mean, I think they are looking for a full solution, but I’d have to say BI as a general umbrella is a very broad, is a very broad topic and typically is viewed initially as sort of the reporting framework of your organization against your enterprise transaction data. Many specific solutions within the business are where people are really gaining insight or around more analytic solutions that are subsets of that data and so I do believe that the trust of the business, of whatever the solution is starts with data and data cleanliness and the hygiene of that data. So that is something that can’t be underestimated in any BI initiative. It’s not as simple as just saying, well, let’s just go buy some BI tools. You have to start with that data but I do think so from an end to end standpoint, you have what problem am I trying to solve within BI and what is the source data that drives it? And then, and then how am I going to present that the result of that in a way that actually I can get insight from? And so I do think that you can subset the problem within this BI solution to what problem am I trying to solve and then get more granular as to what the source data for that is.

Sanjog Aul [00:12:36]:
Now, with what the background that we saw in terms of the challenges that we have, do you think that could be the very reason why a big percentage of decisions, even in fact it as well as business are being made based on gut versus pure BI or using more and more of bi? So do we trust BI for us to really say let me let go of the gut part or reduce the percentage that I’m going to use when it comes to making decisions. So let’s explore this when we come back from the break. Please stay tuned.

Sanjog Aul [00:16:07]:
Welcome back. So Stuart, given all that we spoke in the first segment, it looks like that, yes, we are working and making strides towards getting the BIA under control and things would be good. But there’s so many factors which look outside of control of it and in a way it was also claimed that there are some areas including data cleansing and data which should not belong to it. Do you think that is all contributing towards this issue of people moving more towards still gut feel based decision making versus heavily relying on BI?

Stuart Kippelman [00:16:46]:
There’s two sides to the answer. I think that people are will always use gut in making business decisions as BI gets better, meaning that the tools become more reliable. I don’t mean from an IT side, I mean from a data from the ability to predict and to think like the business. As that continues to improve, you’ll see BI take more of a prominent role in that decision making process where it’s not today. So for example, in one experience that I had we I work for a company where we sold medical devices and those devices contained an enormous amount of data within each device and every night that data was sent home. Basically it was transmitted over the Internet through a secure connection and it was put into databases and some of it was over 100 megs a day per device

Stuart Kippelman [00:18:01]:
so it was an enormous amount of data. It was highly accurate data but BI was not really used. This data was used to do some basic troubleshooting. When a problem occurred, we were able to look at that and say, wow, there’s a real opportunity here. We were able to take that data, mine it. So truly using one of the great capabilities of BI and mining that data for hidden meaning and I believe looking for hidden meaning is one of the true, not just frontiers, but true value creation areas for BI, we were able to actually mine that data

Stuart Kippelman [00:18:49]:
and through a series of predictive capabilities and really looking at the data, we were able to predict failures within hours of accuracy of some of these devices and be able to proactively go out to customers and say we know your device is going to fail within a day, we’re here for a prior service call, we’ll fix this at the same time and it reduces customer, it reduces downtime, it reduces costs on both customer side and on the company side and I think it’s a great example of how BI can truly be used to change the way the business looked and so it moved from a gut, in this case, it moved from a gut feel to a very highly BI focused and accurate feel. That’s something that a human could not look through 200 megs or 100 and something megs a day of data. For every one of these devices sold. You had to rely and Trust the tools, and they proved to be accurate.

Sanjog Aul [00:19:58]:
Now Tony, in your world, how much of this lack of being able to control every portion of how data gets originated, clients qualities maintained and then used in BI and that control not being with us actually prevents you from being able to serve the executive or the business for that matter, in terms of how they make decisions and then how much do they buy the lack of control?

Tony Bender [00:20:28]:
Well, ultimately the business recognizes that there is accountability for the quality of the transactional data and we’ve got some metrics in place that we’re using to monitor data health associated with it. But I think that, so from that perspective, there’s always somewhat of a challenge because the business, no matter what reporting you’re producing, there’s that element as far as data but there’s also an element of doubt that arises from a standpoint of the business analysis that’s put together in order to, to architect how business intelligence will be used and how data will be presented and viewed in a way that will provide insights to the business so that they can actually decide how, you know, what are they learning from this information that is being presented and how has that been digested and acted upon by the business and so one of the other challenges besides data that we find is just clarity from the business of really understanding, connecting the dots between what problem are you trying to solve and making sure that whatever we are constructing together in BI, that we’re solutioning it in a way that allows us to really visualize the data in a meaningful way to gain insight from it and so many of us are visual people and we like to see things spatially and so we don’t like tables of numbers we like things in a visual way, whether it’s a chart or a graph or a dial or something of that nature

Tony Bender [00:22:21]:
but underlying to that are how are we architecting the solution that takes that data and converting it into a meaningful visualization so that you can act upon it. That element is also sometimes a challenge because as we work with a business, it’s not always clear. They may have an end state in mind, but they’re not clear of how to get there and so sometimes we struggle with requirements from the business on what exactly are they wanting to do and how do we ensure that we’re appropriately delivering that through BI.

Stuart Kippelman [00:23:04]:
Just to add one thing to Tony’s comments, I think there’s a lot of value that it can create for it with BI and in a case like that, we own the data, but in the case where we’re providing a tool for the business, there needs to be business sponsorship and business ownership for that data and that data quality otherwise the output is never going to be accurate.

Tony Bender [00:23:30]:
Actually. And just to elaborate that Stu makes a great point is that, you know, sometimes we are very quick as a business, we’re very quick to, you know, to look to technology to solve our problems and while technology is a powerful enabler, but we also have to really be thoughtful about what is the problem and then how do we define what that is and deliver it through the technology, through BI and in that regard, clear business sponsorship and ownership of who really owns this project and how are we going to deliver it is so critical and frequently overlooked or dismissed in terms of getting a fast path to a solution and many BI projects have failed or have underwhelmed the business because of a lack of business ownership and accountability and clear direction from the business around what problem that we’re trying to solve.

Sanjog Aul [00:24:42]:
So while we see that there’s an adoption issue that the very BI project you might have spent millions in or whatever effort that goes into it, it somehow doesn’t get adopted. The reason it looks like is one is they do not trust the quality of what it’s going to deliver, second is the very inertia because they don’t know how to use it or in many cases there might be situations where what they’re thinking in terms of what their gut says is not exactly going in the same direction as what the BI tells you. How much of that disconnect or misalignment has been experienced by people in business and in IT for them to lose trust in the very paradigm, Stu.

Stuart Kippelman [00:25:23]:
You know, the business request, so this gets back down, this gets to the way that it needs to operate and a bit and having a really good understanding, you know, of requirements, as Tony said, is so critical because you will never deliver anything right. If we don’t really understand what the business needs and wants. And just to take that a step further, you know, we kind of, just because of the nature of it growing up, we refer to everyone not in IT as the business and really it needs to be the business. I mean, I think we need to view people, you know, we need to view the way we refer to the business as just other departments and other partners and I think it needs to become part of that front office business. And that means that we ourselves have knowledge and understanding of what’s happening, that we don’t always have to go look and find a particular person

Stuart Kippelman [00:26:26]:
and this is where that business relationship and having really good understanding of the way our business operates, that we’re not just service providers and order takers anymore is so, critical. With that being said, that doesn’t take away the responsibility that we’re building a solution for a business function or to solve a business need and there needs to be someone on that business side that actually can provide their requirements and can provide it in a clear way but IT should be the organization that translates that business speak and we have to understand it into what a technical requirement may be. We should not expect that someone on the business side of the house is going to word things in an IT way which I think is where I’ve seen failures in the past related to projects like this.

Tony Bender [00:27:26]:
Now actually to build on that, I think that that’s a great point is that one of my personal pet peeves is that the business often refers to IT as IT and that we collectively, and they collectively refer to everybody but it as the business.

Stuart Kippelman [00:27:43]:
It’s true.

Tony Bender [00:27:44]:
And I think we need to break all of that down because that’s so far from the truth is that we IT are so, you know, so ingrained in the fabric of the business and a very enviable position position that we can see the business from a vantage point that even the business sometimes can’t see. So very valid points too of really understanding whatever function of the business, whatever their needs are, of really bridging that and probing and not taking at face value what they’re saying and, and really trying to make sure that we’re getting the best results.

Stuart Kippelman [00:28:28]:
Exactly.

Sanjog Aul [00:28:30]:
Let’s take a quick break listeners. We’ll be right back after these messages and see how much time and how much in urgency do we have to make decisions whether big or small and depending on the level of due diligence that you should otherwise be doing. But it is not performed because of lack of resources and or lack of time. So if we are going to be working in this way, so of course the resulting BI related contribution would reduce and that would further have a spiraling down effect where the trust towards BI will reduce and then we’ll again start building towards gut. So is this something that can be controlled? Is this something that we can work towards getting a better handle on? And if yes, how. Please stay tuned. We’ll be right back and explore.

Sanjog Aul [00:32:10]:
So Tony, let’s start with you and when was the last time you had all the time and resources to do all the possible due diligence, get all the best quality data that’s available and then be able to deliver a very good looking product. And when you always have this resource constraint, can you really deliver decision making based on this bi versus having other people eventually resorting to the gut?

Tony Bender [00:32:37]:
Well the reality is that we, you know, we’re always constrained for resource and so we never have ever we never have all the resources or funding that we need in order to get a job done. But I think as IT professionals, the real question is what business problems are trying to be solved and how do we focus on areas that have the greatest impact to the business and so making decisions based on scarcity of resources is a day in the life of any CIO So to a large degree, it’s really trying to understand where are areas of business intelligence or advanced analytics that could be applied that can really raise the bar. An example of that at Alberto that I’ll share is that something that we use for understanding our advertising spend. We’re in the hair and beauty care business, hair care and skincare and so we do a lot of television, print and Internet advertising. And trying to understand the effectiveness of that advertising is very important because we spend hundreds of millions of dollars, tens of millions of dollars on advertising very freely

Tony Bender [00:33:59]:
and we need to understand what the effectiveness of that is. We use some very targeted, advanced analytics capabilities around understanding what kind of lift do we get on incremental revenue or demand associated with advertisements that are done, and using some marketing mix modeling tools and that’s an example where we have to make some choices around where are we going to allocate, spend, and given the size of the prize, where are we going to drive the greatest amount of value? But something like that specific application can drive immense value because we’re spending millions of dollars and the return is significant.

Sanjog Aul [00:34:48]:
Stu, in your world, how many times were you given the time to get the right type of like. Of course, resource constraint. Time is one of the resources, but the sense of urgency, because everything has to be done yesterday and you’ve been told at the 11th hour, how can you deliver?

Stuart Kippelman [00:35:07]:
Well, you know what? I can’t remember a time that I’ve ever had the right amount of resources or funding. But that’s really where Tony said, fantastic. That’s really where the prioritization comes in IT sits in a very unique spot within the company. We get to see everything that happens. So we’re in this position that can bridge the gap between all of the, you know, many of the I wouldn’t say all many of the different departments and divisions and even companies that are part of the organization.

Stuart Kippelman [00:35:46]:
So we have a unique perspective that we can look across the organization and actually connect some of the dots together and that helps us to provide feedback to the CEO and to the board and to the other leaders of the company or really to anyone in. I don’t want to point out a particular level really to anyone in management or decision making capability that would help them to prioritize work that has to be done. So for, you know, example, here at Covanta where, where we’re turning household waste into electricity, our primary focus is the operation and the uptime and the safety of our plants and within IT, we’re able to look across all of these different departments or organizations and not just be a provider of service, but really help the company to see the different, the big picture and all the different pieces related to outages, related to safety, related to how we operate and ways to improve efficiency and that all goes into the prioritization of what IT projects should get done and what priority order and funding follows that. What’s going to have the most, as Tony said, the biggest bang for the buck.

Sanjog Aul [00:37:16]:
You’ve given a choice to you. Would you truly like to see the 100% BI based decision making?

Stuart Kippelman [00:37:24]:
I like to automate everything, but I think there’s a reality to that, that you’re going to always have that gut part of what happens in making a decision.

Tony Bender [00:37:38]:
You know, one of the things that strikes me is that I, you know, I’ve always been a believer of fact based decision making and fact based on the basis of really understanding what your data is and presenting that in an accurate way But one of the things that I’ve learned here at Alberto is that and we do a lot of consumer work as we do for innovation, for new products. We do a lot of what’s called basis testing where we test consumer response to specific new product introductions and one of the things that I’ve learned here is that even in terms of consumer testing is that data and information that comes back from consumer testing really has to be looked at very thoughtfully on the basis of the construction of questions that were given to consumers and how the responses to those questions occur because many times there has to be really some thought given to is there any underlying bias that could be in the responses that are being given by consumers that are really unnoticed by the consumer themselves but because of the way the question is constructed or what have you and so what might appear to be a very fact based decision, upon reflection, could really yield something that’s very counterintuitive and something that really requires experiential knowledge and our CEO has pointed out a couple times in testing that has been done on new products where even with very clear fact based results coming back on consumer response, that those responses can’t be trusted

Tony Bender [00:39:34]:
because sometimes the consumer, even though they’re telling us one thing they’re not really telling us the truth and not, you know, not intentionally, but because of either the construct of the survey or whatever so I think that it is. While it’s very desirable to have a total fact based decision making, I think that there is always going to be some level of experiential knowledge that has to be brought to the table and the gut is going to, you know, is going to win out in those situations.

Sanjog Aul [00:40:11]:
So in all the things that we end up doing here, what are the typical factors that would prevent, besides this lack of clarity, etc, in the data and data quality, which would prevent our decision making from being the best with or without BI? Sure.

Stuart Kippelman [00:40:34]:
I mean, the first thing that comes to mind is not having the support of the organization. So as we were saying before, it’s absolutely critical to have alignment from the company about what you’re doing and the results you’re going to be delivering. That data has to be accurate and without that it’s not going to work.

Sanjog Aul [00:41:00]:
So in terms of. Tony, are you there? So if you were to basically talk about the same issues where the business intelligence portion of it and we are utilizing it, and to whatever degree we still see there are issues and everything else remaining the same, the decision making, the accuracy of decision, the effectiveness of decision making reduces significantly in one situation versus another, in one environment versus another. So why is it, is it like totally a gray and hazy area for us to even play? You there, Tony?

Tony Bender [00:41:42]:
Yeah, I’m sorry. What was the very beginning of that, Sanjog?

Sanjog Aul [00:41:48]:
What I’m basically saying is like I asked too, that everything else remaining the same, are there certain things which prevent decision making to be completely a hazy area or completely a gray area, so that BI could at most come and be an aid, but not completely help take over and make it the best possible decision making that we ever had? It looks like we are too dependent on too many factors. It’s very fluid and BI seems to be one small component.

Tony Bender [00:42:20]:
Yeah. And in my experience, the example that I gave earlier around the consumer and how those, how that information can be put together where you’ve got. Again, a lot of this comes back to your point is the quality of the data that you’re gathering and how much bias that there might be associated with, with events that are occurring in terms of data gathering and in my experience is that wherever you’re doing any kind of surveying that the quality of how the survey is put together can have a significant effect on that in many other transactional elements of running our business. I think we can rely with a fair degree of, confidence in the information that we’re receiving as long as the data that is being gathered is accurate. But in terms of constructing, specific kind of surveys, I mean, sometimes that could lead to bias that you would have to factor out.

Sanjog Aul [00:43:38]:
Let’s take a quick break, listeners, and we’ll be right back after these messages. The thing which we should look at is what if the decision made where you had a very high quality BI solution in place, it goes wrong. So did we use BI to defend that? I did whatever I could do best and I don’t know why did it go wrong? Or are we trying to use really to make sure that increase the accuracy of the BI? What’s the intent with which BI is being utilized and how does that impact what the final results are? Please stay tuned. We’ll be right back.

Stuart Kippelman [00:45:41]:
I’ve Got the Power.

Sanjog Aul [00:47:06]:
So the question here is suppose a decision that was made with a healthy dose of BI related input, it turns out to be wrong. So now who should take the accountability for this failure? Is BI being used to something like predicting weather and then if doesn’t behave it was supposed to snow and it is sunny, then nobody gets fired because we tried to do whatever we could do best. Is that where the accountability should be for anyone implementing and or owning bi? Tony.

Tony Bender [00:47:41]:
Well, I would tend to believe that if you have a BI solution and you get a poor result from it, then obviously in terms of root cause analysis of why did you get the bad result, whatever it was, it tends to bring you all the way back to the data and then how did you solution it? But to a certain degree, and even in advanced analytics there’s always, you know, where you’re using multivariate statistical analysis techniques as an example for marketing mix modeling or trade promotion management or category management in our case at Alberto, there’s always a possibility that you can have, you know, some degree of error. But in terms of accountability, this is another reason why it’s so very critical to have very clear business ownership of who owns this solution from end to end, from data through the solution to the presentation of that data for consumption and insights to action. So I think in our search for answers and improved decision making, BI and it for that matter can’t become, you know, the sole owner of any bad decision that arises as a result of a business intelligence initiative. But we do need to have, I think that that’s why it’s so very critical to have very clear ownership from the business of who’s accountable for this solution.

Sanjog Aul [00:49:19]:
Can we ever have technology be made accountable for a business decision going wrong? And Stu, would you say that you would still want a human being whose neck is to be grabbed if a decision goes bad?

Stuart Kippelman [00:49:32]:
Why? Probably, but it just depends on what the BI tool is being used for. I think BI is one of the many tools in it’s toolbox that has to be applied to the right situation. So I would personally not want a BI tool to be the only decision factor of should we purchase a company or not or should or anything related to a merger and acquisition. I think it’s a critical input that needs to be taken very seriously. But you can’t factor out the experience of people and executives. And at least in today’s world, that’s hard to build into a computer system that is reasonably priced anyway. And, you know, there’s just that level of experience that someone needs to interpret the data. If you’re talking about business intelligence for an operational type of role, like my example of predicting the failure of hardware or predicting business results to try to proactively react to something before it becomes a problem, I think those are excellent areas for BI to not just be part of the role, but in many cases be the.

Stuart Kippelman [00:51:03]:
An automated solution that is actually analyzing data and in some ways acting and really in some ways acting on it. And one example, not in my industry, but there are very sophisticated BI tools that are analyzing credit card transactions. But in the end, the computer is not calling the person who may be defaulting on a credit card bill. It’s someone who is looking at the data saying, look, these flags were raised. Let me call this person and see what’s going on.

Sanjog Aul [00:51:44]:
Tony, would you. What would be your instructions to the person who’s running the BI function? What is that, their challenges, etC, that you’re going to put in front of them? And what’s the holy grail that they’re supposed to aspire for?

Tony Bender [00:51:59]:
Well, in any BI function, I think that it’s very clear to understand within the business what stakeholders are you working for in the business and what problems are we trying to solve, and that we have clear ownership from the business of any work that is being done. So BI is an instrument that provides, that can provide great value to the business if it’s used appropriately. And being used appropriately implies having clarity of purpose. What exactly is it that you want to, what problem are you trying to solve and for whom are you trying to solve that problem? What information are you arming to what individuals and what insights then can they gain and act upon? And so that needs to. BI needs to be looked at end to end from starting with data and clarity around data ownership, not underestimating data, not underestimating solutioning, whatever the BI solution is. And also whoever the end users of these solutions, of making them, putting yourself in their shoes and understanding how are they going to be using these tools. But I think from a standpoint of what we’re looking for is to move BI from what is really just base reporting in our systems, which We’ve produced hundreds of reports that add little or no value to the business, to analytic capabilities that really look at things and correlate multiple events using multivariate statistical analysis and things of that nature and then moving that from not only analytics but also predictive modeling and understanding how do we then predict what will occur based on these variables and the correlation between these variables and then with a high degree of predictability for certain events, the ability to then automate that using business process modeling and management techniques and so ultimately then to where certain events occur that we can trigger other transactions automatically in the system. So I mean, in terms of holy grail, that would be close to where we should be aspiring.

Sanjog Aul [00:54:34]:
Stu, you got 15 seconds. What is your final message for people who are fighting this battle between gut feel and the BI?

Stuart Kippelman [00:54:42]:
I think there’s room for both and neither should be ignored. BI needs to be applied at the right place at the right time to solve the right problem. Focus on priorities. Focus on the biggest ways that having BI can impact the business and bring value.

Sanjog Aul [00:55:00]:
Thank you so much Tony and Stu for sharing your thoughts about this interesting topic with respect to a fight that we always have between gut feel and BI, and hopefully the world out there would understand that while we being human beings, we will never lose that gut. However, if they can use BI, they can just improve the predictability of the results of a decision being made. Thank you so much.

Speaker B [00:55:35]:
Thank you for tuning in to CIO Talk Radio. To learn more about the show, please visit www. Join Sanjog Aul next Wednesday at 9am Central, 7am Pacific for another hour of CIO Talk Radio.

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