Author Archives: thedoctor

Cognitive is the New Buzzword. But what does it mean?

It seems that everyone is talking about Procurement these days. A Google search for cognitive procurement returns about 650,000 results that include news sites, analyst firms, and vendors ranging in size from Old St. Labs to SAP Ariba to IBM.

Definitions are varied as well. Quora defines cognitive procurement as the application of self-learning systems that use data mining, pattern recognition and natural language process (NLP) to mimic the human brain to around the processes of acquiring, buying goods, services or works from an external source. IBM’s Vice President of Global Procurement defines cognitive procurement as the use of systems and approaches that are able to learn behaviour, manage structured and unstructured data, and unlock new insights to enable optimized outcomes. Vodafone defines cognitive procurement as augmented intelligence capabilities that allow a category manager to make faster and smarter data driven decisions that deliver competitive advantage.

But what does this all mean? First of all, the only commonality is using systems to do a task better. Which systems? Which tasks? Who gets the benefits? And what precisely are the benefits?

To figure this out, we have to go back and define what makes for better Procurement. The first step is good Sourcing. What are the keys to good Sourcing?

There are a number of keys to good Sourcing. Some of the most important include:

Visibility. Who are your potential suppliers? What do they provide? Where are they? What do you know about quality, reliability, delivery, etc? What are the risk factors with dealing with them? What data can you get on finances and sustainability? You need good information.

Analytics. Once you get the information, you need to make sense of it. Roll up component and material costs across bill of materials. Amalgamate risk ratings into meaningful scorecards. Aggregate demand across categories. Determine what you need, when, in what quantities, and how much it should cost before you start a negotiation.

Modelling. The ability to define detailed should cost models based on components or materials, production costs that include energy and labour and overhead, and other relevant cost factors. To define how those costs change with market data or production volumes. And so on.

Optimization. Once you get the data, you need to figure out the baseline costs and what the optimal awards are assuming nothing changes. Then how those change as costs change as bids change. Also, what are the optimal logistics strategies and costs. How does logistics impact the award decision? How should the logistics supply chain be designed?

Negotiation Support. At some point, the analysis needs to turn to negotiation, because the goal of sourcing is to acquire the products and services the organization needs to support its operations and satisfy its customers. All of this capability needs to be brought to bear in a cohesive, assistive, fashion that can help a buyer make the right decision.

That’s what cognitive procurement is — presenting a user with the information they need when they need it to make the right decision. Not automated buying. Not artificial intelligence which doesn’t exist. Not trying to mimic the human brain, as we don’t even fully understand how that works now.

So, does any application meet these requirements?

Tealbook … Not Just a Journal Anymore!

When you hear teal, you probably think of the colour which gets its name from the coloured area around the eyes of the common teal, and when you hear tealbook, you’re probably thinking of a notebook in the calming hue of teal, perfect for a journal or personal contact book … maybe even one you can keep your supplier contacts in!

But we all know the problems with a contact book. Contact information changes as people are shuffled around the company. Contacts leave the company, and you not only have to update their information but add a new contact. There is only a limited amount of room for notes. It’s really hard to share the information, and, if your peers are also using handwritten ‘teal journals’, get them to share the information, especially when you need it quickly.

That’s why supplier information management (SIM) modules and platforms were developed. All of the supplier and contact information in one place, accessible to, and updatable by, anyone in the organization. Plus, anyone can search the supplier database for suppliers new to them … but not new to the organization. This was one major limitation. Another was lack of community intelligence from peers. Were they selected or known for certain capabilities, or not? Do they have other customers for a product or service who will serve as references? Are they (now) capable of satisfying a minority designation or certification requirement (in a certain geography)? You can ask this, update the system to track it, but a community keeps this information up to date.

But most importantly, with traditional Supplier Information Management (SIM), you know what you know and you don’t know what you don’t know. You have no way of determining how many potential suppliers you don’t know about for any given category or requirement. Or how good the suppliers are for your needs relative to the suppliers you don’t know about.

That’s where a modern Supplier Information Management with Supplier Discovery platform comes into play. A modern supplier discovery platform, which is more than just a supplier network — as a supplier network is nothing more than a database of suppliers that have been transacted with through a particular platform, allows a community of organizations to keep track of, and provide information and recommendations on, potential suppliers (whether transacted through a platform or not); potential suppliers to self-identify and provide relevant information up front (such as diversity status and certifications); and all parties to share information of potential relevance.

tealbook‘s vision is to create a shared, trusted, supplier base with 100M suppliers that provides a central repository of reliable supplier intelligence that can be used as a stand-alone platform or integrated with your current ERP, sourcing, procurement, contract management, and other spend management systems of relevance through an easy to use API and an interface that is configurable to your organization’s processes and privacy preferences. tealbook already includes 1M vetted, and de-duplicated, suppliers with rich insights and expects to grow daily at an exponential rate to reach 4 million within 12 months.

And while this three-year-old start-up doesn’t have the 100M supplier database yet, they have the solid foundations for a reliable, scalable, extensible, and integratable community supplier intelligence platform that can be configured to your organization’s needs. That is getting the attention of some of the biggest organizations and consultancies in North America.

In the tealbook platform, a user can easily do a search for potential suppliers, review verified supplier profiles, review community generated expertise tags (similar to individual specialty tags on Linkedin), review provided supplier content, create a supplier list for vetting, interact with the supplier to get more information, interact with her teammates for initial vetting and review, and then select a subset of those suppliers for export for consideration in her sourcing/procurement project. And she can do it through the web platform, or the mobile app if she is documenting new potential suppliers at trade shows. Plus the database of connections and employees is always up to date, so she knows who to contact, and who she knows, or knows of, at the potential supplier.

Supplier Discovery (incumbent or new) can be quite time consuming without such a platform. Most organizations would resort to searching online databases, getting recommendations from professional societies, going to events to get information from peers, and so on. Discovery can take weeks on its own when a proper platform with a community built and maintained platform can knock that down to hours. And the information is a lot more reliable than that obtained from a single source. This reduces the time, effort, and risk to discover, pre-vet, and qualify new suppliers substantially — which makes for an improved sourcing and procurement process.

And the search in the tealbook platform is quite powerful — it’s not just keyword, industry, tag — it’s also specific to your data and connections — it’s semantic and it uses machine learning to increasingly improve the relevance of supplier recommendations. And that’s key to identifying the right suppliers for you. And it’s a great choice even if your platform has a basic SIM module. For example, tealbook complements newer sourcing platforms such as ScoutRFP (and eliminates the need for a supplier network entirely), Coupa customers can add on tealbook to fill in the holes in the Coupa S2P platform, and Ariba customers are, as you may have guessed from above, finding it provides that missing piece: mobile, user friendly and socially derived supplier intelligence. With tealbook, they are finally able to rapidly and easily look up updated supplier data, identify and qualify known or new suppliers without going through an extensive process before initiating a sourcing event in Ariba.

In other words, if you are looking to know more about suppliers who have already transacted with your company or regularly need to discover new suppliers (including increasing access to innovative and diversity suppliers) check out tealbook. It might be the platform for you.

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!

Fifty Years Ago Today …

Sweden entered the modern age of transportation when Dagen H occurred and traffic changed from driving on the left to driving on the right … literally overnight! (Those Swedes are masters of efficiency.)

Now if only the UK (and it’s former colony now known as Australia) could get with the times and join the rest of the world. However, given how long it took them to accept the modern calendar, it will probably be another hundred years. But it would make the creation of true global routing software so much easier …