Category Archives: Market Intelligence

BIQ: Alive and Well in the Opera House! Part II

Yesterday we noted that BIQ, from the sleepy little town of Southborough, that was acquired by Opera Solutions in 2012, is not only alive and well in the Opera House, but has been continually improved since its acquisition and the new version, 5(.05), even has a capability no other spend analytics product on the market has.

So what is this new capabilities? We’ll get to that. First of all, we want to note that since we last covered BIQ, a number of improvements have been made, and we’ll cover those.

Secondly, we want to note that the core engine is as powerful as ever. Since it runs entirely in memory, on data entirely in memory, it can process 1M transactions per second. Need to add a dimension? Change a measure? Recalculate a report? It’s instantaneous on data sets of 1M transactions or less. And essentially real-time on data sets of 10M transactions. Try getting that performance from your database or OLAP engine. Just try it.

One of the first big changes they made was complete separation of the engine from the viewer. This allowed them to do two things. One, create a minimal engine footprint (for in-memory execution) with a fully exposed API that allowed them to create a full web-based SaaS version as well as an improved desktop application and expose the full power of the BIQ engine to either instance.

They used QlikView for the web interface and through this interface have created a collection of CIQ (category intelligence) and PIQ (performance intelligence) dashboards for just about every indirect category and standard performance category (supplier, operations, finance, etc.) in addition to a standard spend dashboard with reports and insights that rivals any competitor dashboard. In addition, they have exposed all of the dimensions in the underlying data and measures that have been programmed and a user can not only create ad-hoc reports, but ad-hoc cross-tabs and pivot tables on the fly.

And they re-did the desktop interface to look like a modern analytics front-end that was built this decade. As those who saw it know, the old BIQ looked like a Windows 98 application, even though Microsoft never built anything with that amount of power. The new interface is streamlined, slick, and quick. It has all of the functionality of the old interface, plus modern widget that are easy to rearrange, expand, minimize, and deploy.

One of the best improvements is the new data loader. It’s still file based, but supports a plethora of file formats, can be used to transform data from one format to another, merge files into a single file or cube, picking some or all of the data. It’s quick, easy, user friendly, and can process massive amounts of data quickly, letting users know if there are errors or issues that need to be identified almost immediately.

Another great feature is the new anomaly detection engine that can be run in parallel with BIQ, built on the best of BIQ and Signal Hub technology. Right now, they only have an instance fine tuned to T&E spend in the procurement space, but you can bet more instances will be coming soon. But this is a great start. T&E spend is plentiful, a lot of small transactions, and hard to find those needles that represent off policy spend, off contract spend, and, more importantly, fraudulent spend. Using the new anomaly detection feature you can quickly identify when an employee is flying business instead of coach, using an off-contract airline, or, and this is key, charging pet kennels as lodging or strip club bills as executive dinners.

But this isn’t the best new feature. The best new feature is the new Open Extract capability that provides true open access to Python-based analytics in BIQ. The new version of BIQ engine, which runs 100% in memory, includes the python runtime and a fully integrated IDE. Any analyst or data scientist that can script python can access and manipulate the data in the BIQ engine in real time, using constructs built specifically for this purpose. And these custom built scripts run just as fast as the built in scripts as they run native in the engine. For example, you can run a Benford’s Law analysis on 1M transactions in less than a second. And building it in python, and the Anaconda distribution in particular, means that any of the open source analytics packages for Continuum Analytics can be used. There’s nothing else like it on the market. It takes spend analysis to a whole new level.

BIQ: Alive and Well in the Opera House! Part I

Fourteen years ago, in the sleepy little town of Southborough, Massachusetts, a tiny start up called BIQ was created. It’s mission was to give business analysts the powerful transactional data analysis tool that they needed to do their own analysis and get their own insight. Less than two years later, it released that tool, called BIQ, and it totally changed the spend analysis market. For the first time, power analysts could do everything themselves in a market where spend analysis was primarily offered as a service, and they could do it at a price point that was at least an order of magnitude less than what the big providers were charging them. With licenses starting at 36K a year, an analyst could do the same analysis that he was paying a suite provider 360K for and a best of breed provider 1M for. Now, it required a lot of knowledge, aesthetic blindness, elbow grease, and overtime, but it could be done.

And when we say everything, we mean everything. You could load any flat files you want in a standard format (such as csv) in the data loader. You could combine them into any cubes you wanted by defining the overlapping dimensions. You could define ranged and derived dimensions using simple formula or built in definitions. You could drill down in real time, filter on what you wanted, and export subsets of records. You could define any categorization you wanted against any schema, any mapping rules you wanted, they were organized into priority groups, given a priority order, and run most specific to least specific so you never got a collision or random mapping like you might in a tool where you just defined non-prioritized rules that went in a database and often got applied in random order. You could define supplier families that could be reused. You could build your own cross-tab reports. It was the swiss army knife of analytics, at a price every organization could afford.

This quickly made BIQ a favourite not just among mid-market companies that couldn’t afford, and big companies that didn’t want to afford, high priced services, but also niche consultancies that could now do power-house analytics projects on their own, including firms like Lexington Analytics and Power Advocate. This, along with some really smart marketing, pushed BIQ into the mainstream of spend analytics providers, making it a de-factor shortlist candidate for any company wanting do-it-yourself spend analysis. This, of course, got the attention of many providers, who were afraid of the threat, in awe of the technology, or both.

One of these providers was Opera Solutions, who acquired BIQ in 2012, and shortly after, Lexington Analytics. Once the two providers were merged, Opera Solutions instantly had a complete spend analysis software and services solution for the indirect space. And they have steadily improved this offering since its acquisition. The new version comes packed with some big enhancements, including one capability that is not only market leading, but unique among all the spend analysis providers we have covered to date.

What is that? Come back tomorrow!

To Get the Best Supply Base, Go Beyond the Obvious!

the doctor recently came across an article that said that during the sourcing process, there are many qualitative attributes that procurement teams should take into consideration and that sourcing is about the lowest price, but identifying the greatest value for your sourcing dollars and that one should incorporate multi-factor award criteria into an automated sourcing process. All true. It also provided some examples of the most frequently used qualitative factors, which include:

  • Supplier Market Share
  • Supplier Performance
  • Production & Delivery Capabilities

And these are okay, but they don’t tell the whole story. Plus, sometimes the story they tell is not the right one. For example:

  • with respect to supplier market share, you only care that the market share is big enough to make the supplier financially viable … sometimes the emerging suppliers have the best technologies for you
  • with respect to supplier performance, if you haven’t used the supplier before, and the only data you have is negative data from customers that have gone public, you don’t know if this is the typical experience or an anomaly (like 1 out of 100) and sometimes even how recent the data is
  • with respect to production and delivery capabilities, there’s always a third party partner for delivery

That’s why you need to round out the supplier evaluation components, going beyond the typical, and obvious, evaluation factors, if you want to find the best suppliers for now and the future. Some other factors to consider are:

  • Innovation Capability do they have a track record for innovation and helping customers improve their designs, robustness, product longevity, etc.
  • Corporate Social Responsibility the best supplier from a product perspective could be the worst supplier from a corporate perspective if that supplier uses child labour in the supply chain or buys blood diamonds for their x-ray machines and the story breaks
  • Environmental Risk Profile that examines the supplier from a geo-location, social and political, and economic context which are out of the control of the supplier (whose financial, technological, performance, etc. risk you will be qualifying separately)

And these are valid for all suppliers. When you get into specific categories, you might also want to consider:

  • Services Capability can they support the product, offer consulting services around the product, or streamline the production process beyond other suppliers
  • Six Sigma Black Belt can the supplier help you with your design process or streamline your new product development
  • Supplier’s Supply Chain Design
    is their supply chain more efficient than their peers?

So if you want the best supplier, go beyond the obvious in evaluation.

Procurement and Finance is not a P2P Love Story …

… it’s a bitter rivalry to the bitter end. It’s a feud that makes the Hatfield and McCoy war look like a bitter spat. And you know what, that’s just the way it should be.

Simply put, it’s the CFO’s job to stop spending and it’s the CPO’s job to spend … spend as wisely as possible, but, in a perfect world, spend every dollar that goes out the door that is not a payroll dollar, a lease dollar, a tax dollar, or another dollar that is completely out of negotiable control.

Those job are opposites. Yes, the ultimate goal of the organization is to maximize shareholder value and that is done by maximizing the value of each dollar spent, and both parties are supposed to be working towards this goal, but the CFO, like the CEO, is also beholden to the shareholders, and their value is typically maximized when profit is maximized, and profit is maximized when revenue — spending is minimized, or, in other words, when the CFO succeeds in forcing the CPO to spend less.

And, as we know, spending less is not always the right decision. If the spending less decision results in lower quality, lower reliability, or higher risk, it’s the wrong decision as it will, ultimately, increase (warranty, replacement, service, stock-out, etc.) costs, decrease customer satisfaction, and damage the bottom line to an extent that is many time the short-term cost savings that was obtained from spending less.

But still the CFO will beat the spend less war drum while the CPO beats the give me more budget and more spending control war drum — and this will continue until the end of corporate time. It’s not a love story … it’s a never ending war. And the only hope for tense peace is to find a common enemy — like the enemy of brand damage that can occur if both parties don’t insure that all spend and decisions are made responsibly.