Visibility in EHS

Post written by Peter T., a Management Consultant at Ideaca. Read more on his blog: Visibility.

You might ask yourself, why the focus on Environment, Health & Safety (EHS)? Well, besides the fact that there is a lot of attention on this specific operational area, I feel the industry as a whole has created such a buzz about the benefits of an effective EHS Management System (EHSMS), that organizations are looking at implementing an EHSMS without clearly thinking about the overall value drivers for doing this.

While operationally most organizations have varying EHS needs, the following requirements are often the same: ensuring that they minimize operational risks, sustain and improve the safety record of the workplace, maintain and advance environmental management efficiency, and comply with regulatory mandates. Meeting these requirements however involves designing cohesive EHS processes, a systems integration approach, cooperation across the enterprise, the ability to consolidate information, and a supportive management team that will ensure roadblocks are eliminated or minimized. In essence, a true EHS Management System is beneficial.

However, there are significant challenges that exist when it comes to designing an effective and complete EHS solution. These core challenges are related to data and the specific industry sector. The way data is being managed, collected and utilized is an important component. A common complaint is that there is too much data and not enough information. Individuals seem to be spending more time organizing and finding data than analyzing it. In most cases data management techniques within organizations are not integrated, coming in various forms such as paper files, countless reports, and spreadsheets.

By the time data comes into the operation it is already out of date and not current. It often takes more time to reinterpret and merge current data into existing reports than to redo all the reports over again. Also, tedious ways of doing things and the lack of resources needed to truly re-engineer business processes leaves an operational gap with no big picture of organizational conditions. Departments often work in silos, data and knowledge is not shared across the organization, which leads to inconsistent EHS event handling. These business process, technology and data-specific challenges are further magnified by additional industry related conditions that usually prevent already resource drained organizations from engaging in optimization and improvement initiatives.

So with all these challenges, how do you setup an effective EHS Management System? The key is to identify the core business value drivers of the organization, and ensure that all your EHS initiatives drive to meet these values. These tangible business values can include: increase revenue, decrease costs, operational efficiencies, increase capacity, etc. Intangible value drivers however are significantly harder to prove and require a larger effort to gauge their business value.  These include: expertise, company reputation, employee morale, compliance risk, etc. It is not hard to address a tangible profitability business value.  The value gained from the purchase of a new piece of equipment that will improve operations can easily be determined. Reputation or compliance risks, however, are important non-tangible value drivers. A non-compliance incident can easily push profitability value initiatives to the bottom of the list.

By implementing an effective EHSMS, we can easily monitor and measure all intangible value drivers identified.

Web Analytics supplants Business Intelligence?

Post written by Wade W., BI Consultant at Ideaca. Read more about BI on his blog: Pragmatic Business Intelligence. 

In reading industry material, I recently came across a statement that can only be, in my opinion, the product of tunnel vision. It was one of the most short-sighted and fundamentally erroneous statements I have seen in some time. Analytics

“At the 2005 Emetrics Summit in London, Bob Chatham from Forrester Research described what it means to be the key. He told the assemblage that we are the leaders of tomorrow – and he wasn’t just preaching to the choir to curry favor – he made sense. Chatham told us that “web analytics” would eventually be subsumed into business intelligence, thereby changing the game. Instead of giant data warehouses being sifted in hopes of finding patterns, it would be the likes of us web analysts in charge.” (Jim Sterne, Target Marketing of Santa Barbara, edited by Erika Lindroth, The Weather Channel Interactive, Inc.)

I agree that web analytics will be (and is starting to be) subsumed into BI. However, I question the sentiment that “giant data warehouses [are] being sifted in hopes of finding patterns” and that Web Analytics would “change the game.” Is Web Analytics really going to revolutionize the art of Business Intelligence so significantly? The implication in this quote is that somehow traditional Business Intelligence is somehow inferior to Web Analytics.

I think this is an excellent example of what happens when someone seen as a leader in a field becomes too engrossed in what he is evangelizing…he becomes blind to the bigger picture.

The fact is that Web Analytics, though impressive in its power to aggregate user behaviour and use this to optimize website profitability, it is by nature a limited field. You are able to track user behaviour – generally anonymous at that – through a single customer-facing channel. Web Analytics is Business Intelligence, that only leverages a single source.

“Giant Data Warehouses,” however, are repositories of cross-organizational data, in most cases that extracted from up to hundreds of disparate data sources – Legacy systems, ERPs, CRM systems, finance, operations, HR, desktop apps, web services, external sources – and loaded into a database of a very specific architectural design optimized to return query results on the huge amounts of data very quickly.

Further, this data will certainly have different meanings across and organization – what does “Customer” mean? How do we define this? Part of the process is to work closely with the business to define common business definitions of business entities…so all that data of all that depth and breadth and richness is (should be….) based on common meanings that have been agreed to by key stakeholders. We can mine the data to identify unknown customer segments. We can do Predictive Modeling. Starting with a business mentality, there is the potential to leverage some powerful Business Intelligence.

But I do agree that Web-sourced data represents a substantial opportunity. We can take those Web-specific data sources that power our Web Analytics Apps, and add that to the existing Data Warehouse, passing through the same business rules to ensure heterogeneous data has a single meaning. Now we are talking organization wide, multi-source Business Intellligence.  Plug BI’s powerful analytical tools into our database, and with some targeted, business-driven KPI’s, and we have another, very powerful means of driving profitability

Web Analytics could be said to be proportionally less expensive than traditional BI – same basic cost range for the analytics tool, but less demand for investment in multiple software licenses from different vendors (possibly), less complex data massage (or not…) and shorter time to implement.  And that in itself is a strong argument in favour of Web Analytics – reduced time to market.  However, you won’t have the spectrum of information you have in a well-implemented Data Warehouse.

I believe that Web Analytics is a complement to BI. It can be integrated into a dashboard, or can stand alone to guide developers and webmasters to optimize content. It does have an effect on our database architecture – we must adapt the design of the database to integrate web data. But does it “change the game”? No – it  makes it more interesting. And as a Business Intelligence professional, I welcome another tool that will add value to my service offering and to my clients.

Wade Walker

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