What challenge did OpenBI help your organization address?
We got involved with OpenBI in approximately 2009. We have an internal advertisement system that we maintain, and we wanted to provide reporting capabilities on that platform. In the past, developers have created some reporting capabilities, but they’re very bare-boned and minimal. When people think of reporting, they think they’ll calculate some numbers and out comes a report. Obviously, that wasn’t meeting the need. Our stakeholders and users were getting frustrated because they wanted to get more insights out of their reports, not just understanding the number crunching and the numbers at their face value.
They wanted to look at things in aggregate and by a couple of other dimensions that they had. So, we started looking at different platforms. One of the early contenders was Pentaho, so we decided to use that for our digital advertisement revenue business.
We didn’t realize that until our engagement with OpenBI because we were trying to look for the best partner in putting these together. We didn’t want to hire a consulting firm that put up a couple of reports. We wanted to provide a fully stacked BI [business information] system for advertisement folks due to the frustration. It wasn’t just putting in reporting capability and calling it a day. We had to solve the business problems.
Overall, OpenBI is not like a traditional staff augmentation company. If you already know what you want, I don’t know if OpenBI is the right team to engage. They don’t provide manpower, although they can. They don’t really enjoy just the staff augmentation piece of it, and it’s not where their expertise is, either. They’re not necessarily the people crunching through data just to produce results. Where they do bring in a lot of value is they obviously have a lot of experience in the field. They have done BI for so long that they know inside and out what it really means to put a reporting capability on top of any platform.
With their experience, they can navigate corporate environments easily because they’ve seen so much of it, whether it’s run by technology owners or business owners. They can have that conversation in a very productive way. They combine product development and a strategic mindset into their solution design. They set up the customer interviews and try to understand what the customer is trying to do and wants to do. The days of traditional reports are pretty much ended now. People don’t want to look at the number. There is always an underlying story that they’re really after. If you are a product owner or a decision maker, it’s rare that you check the numbers just for their face value. You can check to see if the promise of, say 35,000 users being redirected really occurred. This is different from trying to understand how you prioritize the product development, and how you take the insights from your data to come up with better and more compelling products. To me, that is the hardest part.
A very experienced analyst who has been with the company for a long time, or who has been in that situation for a long time, can really tease out those questions from product owners, business users, or stakeholders, and business intelligence is very much a technology department. By stakeholders, I really mean business users who are essentially funding this work. It’s hard to get them to get them to tell us exactly what they want. Often, business users think they need to speak your language, the language of data and technology, in order to get what they want out of it in that process.
The problem is that they turn their questions into technology solutions, which isn’t what they want in the first place.
Many times, when people talk to technology people, they say they want to be able to see the distinct users by any ad campaign on any particular content type, or content category that’s on our side by the author of that content. Because of the nature of BI, you really can’t do that because that means that if you want to count users, you have to keep data at the lowest grain. The volumes that we deal with for the users, the cardinality of that data would have been impossible to accomplish a few years back.
This is opposed to really understanding what data is needed by the trafficker of the advertisements, operations manager, or ad sales staff, so they can do their job better. They don’t necessarily need data in every single permutation. Because they’re trying to fold it into a technology question, they end up designing a solution that may not necessarily work for them. On the other hand, OpenBI was able to hone in on customer satisfaction.
Also, they look at open source technologies more favorably than closed source technologies. It’s a tremendous benefit for any organization to go toward an open source solution. Obviously, saving money is a big win. There is a bigger win than that. Many people don’t realize that the newspaper is more of a technology company than a media firm. Any company that has a big reliance on technology will have a big developer shop. In that engineering culture, open source technologies are part of the culture for retention, for creative development, for growth. This is what excites engineers. I think that was the best investment we made, in looking into a lot of open source tools. Our company has released many open source tools.
In our experience with OpenBI, they are slightly more expensive than an offshore firm. I think the quality certainly speaks louder than words. They bring so much quality to the table.