September 2007
By Steve Latham, vice-president, TietoEnator Forest
One of the challenges for multi-mill operations in the pulp and paper industry is ensuring the uniform reporting of key performance indicators (KPIs). Various operations have different data collection mechanisms, different data definitions and even different KPI formulas. What can information technology (IT) do to help address the challenges of system and process uniformity before the calculations even begin? And, once begun, what methodologies can be used to ensure uniformity?
Making measurements fit objectives
Pulp and paper companies have various methods to measure operational excellence: paper machine efficiency, mill efficiency, time efficiency, etc. For the most part, all of the methods are valid because performance is a relative measurement. How did we perform relative to the ideal? How did we perform relative to our best? There is no magical baseline of performance standards. The TAPPI standard measurements are well defined, including the newly recommended area efficiency and capability measurements that are normalized using machine deckle for comparison across machine types and mills.
It all starts with the common saying, "you can't control what you can't measure," and its corollary "you get what you measure." Business leaders need to understand their objectives and make sure that the measurements fit those objectives, especially if the values are tied to performance reward. For example, to measure pure paper machine performance, trim loss should be excluded because it is outside the control of the paper machine crew. However, to measure company performance, trim loss should absolutely be included in the formula.
Business managers need to understand, in detail, every value used in their relevant KPIs. This seems obvious, but in the paper industry there is a bit of the attitude that "we have always done it that way." A manager may have understood "the numbers" in the past, but not revisited them as evolving strategies and IT projects introduce change.
A good example of this is an efficiency based on actual production over potential production, where potential production equals: basis weight x speed x deckle x time. Is the speed the actual weighted average speed over time? Or is it the target speed for the basis weight (also a weighted average over time)? Using this formula, the machine may have run more slowly than normal, yet the efficiency looked fine. Knowing the formula is not enough. A detailed knowledge of each value and its meaning is necessary to define business targets.
Once the numbers are clear, targets must be defined for each KPI. Here, IT and business management face another decision. Are targets based on individual values for every KPI? For example, is there a basic target for paper machine efficiency? Or is the target based on the grade mix over the time period? The targets, along with robust KPIs, lead to a balanced scorecard that provides a consistent, relative view of operational performance.
Delivering reliable KPIs
Now that the KPIs and the data supporting them have been defined and understood, the information technology portion of the task comes into play. The basic building blocks of the KPIs need to be collected across the enterprise, which often includes multiple systems and technologies. Targeted values for KPIs usually need to be stored, maintained and/or calculated. IT then needs to deliver the KPIs to the business in a simple and uniform way and be prepared to answer the question "what's in this number?" when managers don't like what they see. Over time, if the collection and integrity of the data is sound, these inquiries will decrease as trust in "the numbers" builds.
In business operations, IT must make sure that ironclad rules are defined for all KPIs affected by operational decisions. These rules then must be communicated throughout the operation. For example, clear and concise definitions of rules for downtime (what counts as operational downtime), "A" grade production, on-time shipment, etc, are required. A yearly audit of KPIs at points where production data is collected is recommended to ensure each operation follows the same rules. Over time, understanding of the original KPI project will fray. A yearly audit of base data helps maintain the integrity of the balanced scorecard.
In summary, ensure the KPIs fit the company strategy and goals. Make sure all decision makers understand the KPIs relevant to them in detail (even if it requires training) and make sure there are rules that all areas of the operation follow. IT then needs to deliver on those KPIs in a reliable and auditable fashion to drive business improvement throughout the project.
Pulp & Paper magazine is FREE to qualified subscribers. Click here to find out more.
