Big Data is seen as an asset, a weapon that can be wielded for disruptive advantage, and yet one of the biggest challenges to unlocking its potential is the lack of available tools, and even more importantly solutions to help companies tackle it.
HADOOP, Data Scientists commanding as high as $300,000 salaries, and even luck, dominate the scene today. It is an esoteric, expensive, and risky proposition.
Based on my professional experience as Chief Information Officer what makes Big Data come to life is understanding how to translate use cases into value. For the most part, it is an art and science that blends creativity and a curiosity with information technology expertise, executive leadership skills, and business acumen.
That said, serendipity is nice, but sustainable advancement occurs through deliberate intention, with a demonstrated return on investment. It is here that technology solutions excel.
Technology solutions anticipate business problems and challenges, and can therefore guide companies. In the case of Big Data, solutions ideally should drive insights into problems or opportunities to unlock value. They must get to the real crux of the question what can Big Data do for me?
Enter Profitect.
We talked with Profitect CEO, Guy Yehiav, about how Profitect saw this opportunity to disrupt the Wild West of Big Data and built a targeted Retail Big Data analytic solution.
Profitect engineered their offering to anticipate profit drivers in Retail and to guide companies to take meaningful actions from Big Data derived findings. Companies such as Ahold, Abercrombie & Fitch, and others are all benefiting from their use of Profitect.
When Guy joined Profitect, it was a hybrid consulting/software group revolving around Big Data with a focus on delivering retail profitability. Now, Profitect has evolved into a powerful solution that takes a unique approach to Big Data, patterns as opposed to aggregation, value as opposed to aggravation.
We will present a three part series for you from our talks with Guy. In this article, we focus on how Profitect engineered their solution and the key paradigms they built into the system that really speak to how companies can succeed and drive value from Big Data.
INTERVIEW
eCommerceCIO: Guy, can you help us understand your vision for Profitect? Why did you progress the company from a consulting orientation to a solution orientation?
Guy: I joined in 2010 with a very clear idea of wanting to take what Profitect was doing – the value-creating part of it – and improve it by automating and democratizing it. This means we had to turn what Profitect was doing in consulting + software to an off-of-the-shelf solution that could be implemented quickly and easily.
In some ways, it is similar to what I did with my prior company Demanta, which is a Supply Chain, Demand Management, Trade Promotion Management company that we sold to Oracle in 2006. As part of the deal, I stayed on with Oracle for four years in their Supply Chain offering. I eventually left and began doing some work with Venture Capital. When we came across Profitect, I saw it as a breath of fresh air, and a chance to do it again.
Profitect uniquely understood what, in my opinion, has been missing all along – a “Descriptive Insight Engine”. This is a challenge for not just Retail, but all Supply Chain solutions. And, it’s something that everyone in supply chain would struggle with in our prior lives.
If you think about what happens with Sales & Operation Planning, Demand Management, and Trade-Promotion Management tools, they provide great reports and insights into the future. But, they require uniquely talented supply-chain resources to understand the reports and then to create actions out of the information, which have to be communicated and coordinated across multiple parties in different functions.
This operating model inevitably leads to delays in action due to timing of communication between the various parties involved, not to mention the issue with Supply Chain talent attrition, which was, and is, high.
For instance, it may sound like a good problem to have when Sales is outpacing Supply, but it creates customer satisfaction issues. Out-of-Stocks can be a kiss of death in some cases, or a Profit Loss event at the very least.
The Sales & Operation planning discussion would have to be coordinated by these Supply Chain resources, who would have to get everybody on the same page – the Supply guys to obtain more, the Sales guys to sell to supply levels. It is a difficult balancing act, made all the more difficult when the Supply Chain talent leaves for a better paying position.
Profitect saw the problem with this operating paradigm way in advance, way before big data was cool, and had the unique idea of finding the golden nuggets within the massive amount of data Retailers specifically generate and maintain, and to send them the findings, not as a report but as a descriptive insight.
Furthermore, Profitect saw the need to take another step beyond the reports and the descriptive insights, and to deliver the relative best practice related to the insight that will generate the right action.
In Retail, this question of best practice is a very important matter, and it is Company Culture guided. In other words, the Best Practice for generating dollars out of a value opportunity at Target may not be the same as at Macy’s. New talent going from Target to Macy’s for example needs to be able to very quickly adapt to the Macy’s Best Practice way of doing things, or vice-versa. Profitect solution captures, houses, and provides that guidance.
This shared vision is what attracted me to Profitect. Let’s not just take the big data and solve it, but let’s take another step and provide a descriptive insight on what’s wrong, and then another step to provide a prescribed action on what to do to digest and deliver a dollar value to the company.
It is very advanced vision, and I found it, and still find it, very refreshing.
eCommerceCIO: Are there other solutions out there on which you modelled your offering?
Guy: I looked at a number of companies and did not find any who have purposely built a solution that delivers from Big Data to Descriptive Insights to Prescriptive Best Practices. They are just not out there. But, many people talk about it, or say they offer it. So, the idea is out there, even if nobody else is delivering it.
One member of our Board who is a Retailer and industry veteran told me – there are 30 years of lies we are fighting in selling software in Retail. Companies have claimed to do some of what we do, but they are not doing it, resulting in under delivery. By the way, he was a Profitect customer first before joining our Board, and has a long history at looking at Retail technology solutions.
eCommerceCIO: If nobody is doing what you are doing, it must be too hard of a stretch for the market. How can you expect customers to adopt it?
Guy: What we do is complex, but that is behind the scenes. If you look at the success of SalesForce, they are complex at the back end as well. The main reason for their success, compared to the other CRMs at the time, was their intuitive, ease of use from the user perspective. It is like Google search – only one entry box at the front end, while all the complexity is hidden in the back, obviously not easy to duplicate.
From Implementation through Training to Use – it all has to be quick, easy, and intuitive.
We took that lesson to heart at Profitect, and have engineered our solution accordingly.
Compared to most Big Data implementations, where you are talking at least the better part of a year if you can get the right resources with the right experience, we have totally taken that time, cost, and complexity out of the equation.
For instance, we recently brought up a multi-billion dollar retailer in less than a week on Profitect. [NOTE: Guy shared the name off the record, but as of this writing did not want to release the name due to company agreements]. They were blown away! They literally said “Wow! That was just amazing!”
Show me another Big Data implementation timeline that can occur so quickly. You cannot. They are not out there.
eCommerceCIO: How did you engineer the solution?
Guy: We are a cloud-based solution. This is a part of the reason we can deliver so quickly. When we started, the business concept was great, but we were more of a consulting business leveraging a BI solution. We would go to the Retailer, do some analysis, and build some custom solutions for them.
Frankly, this approach took a lot of time, and it was not scalable or repeatable. We could not go to the Big box retailers of the world, and expect to do business with all of them. Our resources would get committed to one account, and that would be that.
And so, understanding that our technology platform and stack would enable our vision, one of the first charters that I had was to build an R&D center, and a platform with our own stack that we can advance and innovate in a modular fashion; that would serve as a SaaS model with the goal of being able to bring customers up very quickly on our platform.
We pulled together an amazing R&D team, with a great R&D leader, and we got to work, and delivered the great solution we offer today.
eCommerceCIO: You mention intuitive ease of use. How exactly did you achieve that?
Guy: Once we had our SaaS center running, we started to focus on the application stack itself. We wanted the functionality to be owned by the business and not just by IT. So, we intentionally minimized any coding for configuration by providing a business modeler that enables our users to change configurations, securities, statistical benchmarks, and other areas. Basically, users own their own destiny. They don’t need to call IT or even Profitect to make desired changes. It is all about easy configuration that drives satisfaction.
eCommerceCIO: What sort of subject-matter expert typically works in Profitect from a company side? And, how does a company best organize around your solution for success?
Guy: This question of organization is very important, and it drives a lot of how we have engineered the Profitect solution. When you look at some of the reasons why Big Data or other Analytic initiatives succeed or fail, alignment is a key issue.
You can find a number of examples where companies will have a Big Data team sitting outside the functions they are to support. On paper, it makes sense as a shared service, but when it comes to generating action based on insight, this structure falls down.
We have a customer who had tried this structure before adopting our solution. Their Big Data team was very smart, very capable, but they were not properly aligned with the rest of the business. They sat outside the natural lines of inner and cross-department communication, and the initiative failed to deliver value despite the insights the team generated.
We purposefully gear our modules to match the functional roles in Retailing, and to tie them together as virtual task teams. We anticipate the organization and deliver the relevant descriptive insights, both structured and unstructured, guiding it through the application to the functions that can consume it and act on it.
Marketing, Merchandising, Finance, Store Operations, Loss Prevention, Logistics, etc. We support each piece of the entire operation with the right information, the right descriptive insights, and the relevant best practices for each role, taking cross-functional processes into consideration.
In short, each department owns their data, insights, and best practices, but then we coordinate them for matters that cross functions, our customers like to call it “The Profit Hub”.
For instance, we approach Margin as a cross functional task coordinating financial analysis, merchandising, marketing, and store operations. Another example is how we approach On-shelf Availability. In this case, the task-force team would be supply chain, loss prevention, and store operations.
We find that sticking to standard-operating procedures in retail, with cross functional teams that are enabled with a pocket of analytics, work much better than an isolated big-data analyst team that has all of the smarts but is outside the natural lines of communication in the business.
Again this question of alignment is something that you and I have seen in Supply Chain Planning systems in the past, and it has not changed with regards to Big Data.
Please stay tuned for our next article in the series, “Retail is Detail when it comes to Big Data”, where we will explore in more depth with Guy Profitect’s unique approach to how they specifically tackle delivering value from Retail Big Data.
In the meantime, for more information about Profitect, please contact fran@profitect.com
– See more at: http://ecommercecio.com/big-data-profit-patterns/#sthash.Cf04BdOC.dpuf
John Stern is the founder of eCommerceCIO
The post Big Data is Ripe for Disruption appeared first on Profitect.