Big Sky Thinking

Many organizations, especially IT organizations, are extremely effective at collecting information. This isn't a good thing. The data comes in heaps, with no purpose or structure, and often gets dumped into an unimaginably complex and lengthy powerpoint presentation or built into a dashboard that is at best interesting and at worst shuts down the higher brain functions.

How can an executive cope with the deluge? I am a big fan of crisp, simple visuals. Avinash Kaushik over at Occam's Razor recently posted an excellent example of how a visual can make an enormous difference in making data decisionable. The post features a great graphic depicting the breakout of the federal budget.

Avinash's post is a recent example of what a few have known for a long time: proper visualization of data is critical and it's not easy. My favorite tome on the subject is Edward Tufte's The Visual Display of Quantitative Information. You can also locate Mr. Tufe's website here.

In my view, which some may view as counter-intuitive, the visual can be an excellent starting point for designing a decision making process and a data collection program to support it. If you are an executive, especially a visually thinking executive, try the following steps the next time you are facing a complex decision:

1) Set the decision goal - what's the outcome this decision is intended to resolve or advance?

2) Draw, by hand, a picture that would contain 80% of what you'd need to make the decision. It might contain the criteria, the data sources, the players, or any number of other influencing factors. Don't be afraid to sketch if you (like me) can't do much better than stick figures. Don't worry about accuracy.

3) Hand the picture to your corporate or organizational metrics or business intelligence POC. Tell him or her to turn around a 60% accurate representation of it within 24 hours. If they look puzzled, there's a good chance that either a) they don't know how to represent corporate data in a way that is decisionable or b) you are an exceptionally poor artist. "SAP doesn't present that report" is no excuse.

4) Iterate the picture until it's accurate enough to make the decision in question on an ongoing basis. It might be hard to get the first couple done, but keep at it. Once the organization has rewired its neural pathways to get the report done quickly, it should be a breeze to repeat.

James Taylor over at Enterprise Decision Management has written a nice summary of a recent interview he completed with DMReview on "The Art of the Decision." James' piece is a very nice complement to Manoj' post below on the appropriate unit of analysis for decision making.

Manoj explains with great clarity the importance of using processes as the unit of analysis for decisionmaking. This allows organizations to avoid organizational conflicts and maximize the leverage of the decisions it makes.

James' post goes on to explain how, once quality process design is in place and is the basis of continuous improvement, additional gains may be made by focusing on incoming data and metadata. Manoj also states, "any meaningful action plan would have to focus on coordinating the entire supply chain all the way back from customer orders, to the distribution center, to the manufacturing plants, and then to the suppliers." The point: an organization can learn a great deal, and dramatically increase decisionmaking efficiency, by knowing something about the very first pieces of information that come in the door.

Manoj's and James's posts present a compelling argument: making maximum use of the data incoming from a customer (or at the process initiation) can avoid decision conflicts and errors later on in the process. In Manoj's post, an organization had trouble when decisionmaking was being done at three levels of the organization simultaneously. The shift of focus onto a process as the unit of analysis, combined with making proper use of the data initiating the process, can reduce those conflicts and improve the process result. The process and the information within it become as valuable as the goods and services migrating through the process.

This question is often posed by managers and consultants alike in addressing decision making situations they encounter. The unit of analysis often refers to the level of the organizational unit around which the decision making models are built. The conventional wisdom has been to do the business planning analysis at the strategic business unit (SBU) level, group analysis at the team level, and operational analysis at the individual employee level. While intuitively reasonable and logical, it is possible to bring all these different levels together if the analysis is done with the key process being the unit of analysis. It promotes better decision making, cuts across organizational silos, and applies the maximum leverage in producing the desired results.

Let me illustrate this concept through a decision-making situation I encountered. A business unit of a Fortune 500 firm was experiencing delays in filling customer orders, many of which were distributed between both domestic and international clients. Inventory levels for finished goods were high, while at the same time order fill rates were stagnant or declining. The distribution center was full with inventory spilling over to the tractor trailers parked outside the warehouse. The trailers were more or less being used as long term storage areas. Profits were down to the point where at least one of the manufacturing plants was considered less than viable despite having becoming more efficient and productive over the course of years.

In an improvement initiative, a top level management team was created to analyze the underlying problems with the objective of stemming the tide and improving the bottom line results. Representatives from different functional areas offered opinions and insights as they saw fit. While these suggestions were often correct and factual, they failed to provide a complete picture. It appeared that decision making analysis was simultaneously being done at all three levels – organizational, group, and individual. It increased decision making complexity without the emergence of a coherent plan of action that could unite different view-points and decision making levels.

A more tractable means of analysis was found when the “order taking and delivery” process was defined as the unit of analysis. This process was mapped for both domestic and international orders, and nested process maps were created wherever appropriate. In this fashion, one could work all the way down from the top organizational level down to the group and individual level. Redundant steps were identified that unnecessarily lengthened lead times. One such step for instance was doing credit checks on all orders irrespective of the financial reliability and payment history of individual clients. While fiscally sound, it created unnecessary delays and expended organizational efforts. Similarly, mismatches were identified between shipping schedules from international ports and actual delivery schedules from a regional warehouse where all customer orders were assembled based on shipments from different manufacturing plants. Only through such a process based analysis, which also questioned long standing procedures, did coherent insights finally begin to emerge. It was more an issue of matching demand information and product flows, rather than viewing the overall problem as purely a marketing problem, or a manufacturing problem, or a distribution problem. Any meaningful action plan would have to focus on coordinating the entire supply chain all the way back from customer orders, to the distribution center, to the manufacturing plants, and then to the suppliers. The management team would not have got to this point had they not identified a key process that impacted their desired objectives, and then made its improvement as their unit of analysis.

When in doubt or confusion, always look towards identifying and analyzing the key underlying processes in order to make headway and achieve decision making clarity.