Getting started in Business Intelligence (BI) on a budget

This is a simple demonstration as to how you and your firm can get started turning the data that you already have into the information you desperately need using tools you already own. The task of turning data into information for decision-making is the essence of business intelligence (BI).

So, here we go.

Everybody has data

Everybody has data. Many companies are wallowing in data. What they are lacking is “information.”

Read my posts here and here for more about the differences between data, information and knowledge.

Quick! Take five or ten minutes to peruse the following table of data and write down everything that you see in these data to help make decisions about the firm’s future.

I will give you one hint: the column identified as ‘ARPAC’ is “Average Revenues per Active Customer.”

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Okay. Times up.

Hold on to your list.

Turning data into information—simply, easily, cheaply

In order to produce what follows, I used only Microsoft® Excel™ and its native ability to access databases to fetch and refresh data.

Here’s the first graph I produced:

This is nothing more than a simple bar graph of column “SOSales” (Sales Order Sales, as opposed to Invoiced Sales, for example) shown in the data above. I used Microsoft’s native capabilities to add a “trend line.”

By looking at this simple graph, several questions might come to mind that would bear further investigation:

1. Why have our monthly sales dropped from just over $8 million a month to an average of about $6 million per month over these 29 months?
2. Why or how were able to produce about $11 million in sales in July of 2008? What did we do differently? How can we build on what we learned in that experience?
3. Is my drop in sales related to lost customers?

The next graph that I produced looked like this:

This graph answered my question number three above—at least partially. Month-to-month our firm has stayed pretty steady in terms of the number of active customers served. The firm is hovering right in the 250-customers-per-month range.

On the one hand, that is good. It means the firm is steady in this regard, but it does provoke other questions that would need to be answered through further digging:

1. We are serving about 250 customer per month, but is the same 250 customers, or do I have high turnover rates for customers?
2. Are we constantly having to spend precious marketing resources to capture new customers, or do we have a high volume of repeat business?

But wait! If we are not loosing customers (at least in numbers), but our sales are falling off (in aggregate), what is that telling us?

The third graph I produced was “Average Sales per Active Customer” (month-to-month). This graph clearly shows that between January 2008 and May 2010, the firm’s average sale per active customer fell from about $32,000 per customer to under $25,000 per customer.

Here again, this graph immediately provides clues worthy of further, more detailed, investigation:

1. Are these different customers buying less product? Or, are we serving pretty much the same customers, but they are just buying less from us?
2. Either way, we should figure out why: Are they buying similar quantities, but our prices (and, perhaps, margins) have shrunk over this period? Or, are they buying smaller quantities of merchandise or services from us?
3. Either way, we should find out why: If they are buying smaller quantities, is some of that business going to our competitors?

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Next steps

As you can see, turning the data into information allows our mind to quickly digest it and move toward decision-making. In some cases—perhaps many cases, when you first start—the process will lead to further information gathering.

On the other hand, you will sometimes discover that tribal knowledge already present in your organization will help you take immediate steps to begin making more money tomorrow than you are making today. Frequently, those steps involve no investment at all. Sometimes all it take is understanding better what is happening. Other times, a simple policy change permits significant increases in Throughput and profits.

After all, isn’t that really what you want to do—not spending six-figures on a new business intelligence “solution”?

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Read more here about unlocking “tribal knowledge.”

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How I did it step-by-step

1. Identify the data
2. Build a SQL Server view or query
3. Connect Microsoft Excel to the data
4. Build the graphs

Total time: about 2 to 2.5 hours

ERP Vendors and Customers: The Blind Leading the Blind

Writing in CIO UK magazine online, David Henderson’s article entitled “Why IT vendors must raise their game” makes several salient points. Not least among the points raised is the fact that “too many IT vendor sales personnel don’t really understand my underlying business processes and investment criteria….”

For me, however, the issue is somewhat stood on its head. Far too many business enterprises with which I have been involved have precisely the same problem internally. CEOs, CFOs and CIOs in many businesses buy new technologies without understanding their own underlying business processes and by what criteria they should invest.

What executives and managers should know

Executives and managers seeking ways to improve their business enterprises (read: make more money tomorrow than they are making today) too often buy new technologies out of “hope” or “desperation,” rather than with a clear and concise understanding of

1. WHAT needs to change in order for the business to begin making more money tomorrow than it is making today;
   
2. What the change should LOOK LIKE; or
   
3. HOW to effect the change (including what role any new or upgraded technologies might play in delivering the improvement).

Since they do not have the tools to concisely analyze what needs to change in order to make more money tomorrow, then they cannot know what the change should look like or how to bring about the change effectively. So, in the absence of clarity, they grope about in their darkness hoping that some change – any change – will bring them their desired end of higher profits.

Blind leading the blind

Like the blind leading the blind, the technology vendors and resellers who do not fully understand their prospects’ underlying business processes or appropriate criteria for investment (in fact, they understand them less clearly than the executives and managers, in many cases), console the yearning executives with platitudes and “rules of thumb” about how their latest and greatest “gee-whiz” technology will “reduce costs by X percent” and “improve sales by Y percent.”

Of course, this is precisely what the executives want to hear. Like the Sirens of old, the vendors and resellers lead many to spend. Even if they don’t fully believe what they are hearing from the vendors and VARs, the executives and managers frequently do not take time to calculate with any precision just how or why the new technology should, could, or would produce a return on investment (ROI) in their particular organization and circumstances. Instead, they close their eyes and ears to any negative thinking and, In the absence of any better ideas, these executives take out their checkbook to purchase the latest and greatest of new technologies. Of course, the correct general ledger account to which this “investment” should be charged is “Hope and Earnest Expectation.”

Serendipity

Sometimes good things come of this method. According to the industry literature, we can say that about one out of three such “investments” lead to noticeable improvement. Many times, however, the measure of improvement cannot be known with certainty. A growing company that shows improvement after some implementation cannot know which results may have occurred even in the absence of the new technology. A far greater share of SMBs (small-to-mid-sized businesses) simply assume they are “better off” if they are not clearly “worse off” following the deployment of some new technology. Some merely breathe a sigh of relief after some trying implementation period and, like a good Calvinist, say, “I’m glad that’s over,” without ever looking back to measure their return on investment.

My argument, however, is that “hope” and “serendipity” are not strategies and, while a few companies come to excel and even to dominate some markets for a short period of time based on little more than serendipity, it is not a sound strategy for long-term growth in any enterprise. For executives and managers return on investment should be seen as a primary responsibility. This responsibility should not be handed over to the technology vendor or VAR (value-added reseller). Neither should it be left to chance.

As W. Edwards Deming said so clearly: “It is management’s job to know.”

It is management’s job to figure out WHAT needs to change in order to start making more money tomorrow than the firm is making today. It is management’s job to come to a clear understanding as what that change should look like when it occurs. And, it is management’s job to define an unambiguous roadmap to effecting the necessary change. Then, it should be management’s job to measure and report on the return on investment yielded by their own keen insight.

Need help with this? Contact me at rcushing(at)GeeWhiz2ROI(dot)com and let’s talk.

©2010 Richard D. Cushing

The New ERP - Part 4

What executives and managers in most organizations lack is a sound "theory" about how their own organization works and responds to its environment as a "system." They know how each department works -- more or less -- but they have never really stopped to think how the "system" works as a whole.

Asked directly, most executives and managers could not tell you -- with specifics -- why three of the initiatives that they have undertaken in the last two years seem to have delivered some improvement (but not all that they expected). Nor could they describe for you precisely why another five of the initiatives they labored over delivered no measurable results -- assuming that they actually did no damage to the organization. (Of course, this whole conversation assumes that you can actually get such executives or managers to admit that things they tried produced no results, in fact. Generally, they have willingly pushed out of their mind those matters over which they have expended precious time and energy to no effect -- only to give up in disgust. Then they tried the next management fad in its place.)

"I am not yet convinced regarding the connection between 'knowledge' and 'theory,'" I hear you saying. Then consider this:

How many people had seen apples falling from trees (or witnessed similar events) for how many hundreds or thousands of years before Sir Isaac Newton postulated a "theory" about a force we call gravity? Everyone had experienced gravity and everyone had information about the effects of gravity, but until Newton, no one had any knowledge about gravity.

Once the "theory" was set forth, cause-and-effect experiments could be developed to measure the effects of gravity. Based on the results of these experiments, one could then postulate if-then correlations: if we do X, then Y should be the result.

If management is anything, it is about being able to propose actions with a predictable -- not random -- effect on the "system" to which the action is being applied.

But, what of the second wrong assumption in the chain of reasoning (in the prior post)?

It should be clear now that it is not more information that will help us manage better. Rather, it is a sound theory or logical framework by which to understand how the "system" functions and interacts with its environment. The second wrong assumption is, then, "More information means we can manage better."

The correct approach would be to say: "If we can develop a sound and effective framework or theory by which to interpret the information coming from our organization (our "system"), then we will be able to manage better."

And, since developing a theoretical framework is likely not a function that will be much enhanced by technologies, then the next step is not to rush out to buy new software or hardware. Clearly, the next step should be to find a way to develop such a sound theoretical framework.

[To be continued]

The New ERP - Part 3

Failure No. 3: Substantial -- sometimes even huge -- budget overruns
Unfortunately, the causes of the "go-live" delays typically are also the major contributors to exorbitant budget overruns, too. Executives and managers that have lost sight of specific and measurable objectives -- or they never had any such objectives in mind from the beginning -- are likely to make many foolish decisions related to customizations and modifications. Having lost focus -- or never having had any focus -- such projects will soon take on a life of their own. Managers may be incapable of bringing them back under control without the direst of actions.

Failure No. 4: Stopping or slowing production and delivery
This is clearly the worst-case scenario: the very technology investment undertaken with some vague and likely unquantified hope of delivering business advantages becomes an albatross around the neck of the whole organization. Rather than delivering a "sustainable business advantage," the new technology bogs down or stops the organization's ability to produce Throughput entirely.

Almost without exception, this dire result can be traced back to a poor understanding of the organization's real situation prior to the decision to deploy new technologies. The circumstances may be further aggravated by the fact that the organization did not obtain a valid proof-of-concept from the technology vendor before the purchasing decision was made and the Everything Replacement Project (traditional ERP) undertaken.


The Everything Replacement Project (traditional ERP) decision to buy

Since the introduction of the computer especially, executives and managers with money to spend on technologies have often carried about within themselves a peculiar mindset. That mindset tells them, "If I just had more data; if I just knew more details about my enterprise, then I could manage better. In fact, if I could know in detail everything about my enterprise, then I could manage perfectly."

Of course, traditional ERP (Everthing Replacement Project) vendors prey on this mindset. In fact, they often help instill and solidify this mindset within their prospects and clients. As a result, the decision-making process regarding whether executives and managers should buy new or more technology often follows along these lines:

There are at least two incorrect assumptions in this chain of reasoning.

The first wrong assumption is that "information" is the key to better management. Information is not the key to better management. Knowledge is the key to better management and information is not knowledge.

Data gathered and presented by technology is a representation of what your organization has experienced. That experience (history) may include what you sold, some cost data, some profit data, data about your expenses, and so forth. However, as W. Edwards Deming put it so plainly, "Experience teaches you nothing without theory." He also said, "Knowledge comes from theory."

[To be continued]

Contact me!

...

The danger of "We know!" - Part 3

In this portion of our series, we're going to talk about how to put a "framework" or "theory" around what you already know about your business enterprise. This is not an exercise in "business theory." This is a real and practical approach to gaining effective control of your enterprise after (perhaps) years of "muddling through" with more or less mediocre results.

One of the reasons executives and managers are not able to really "understand" what they "know" about their own organizations is that, since they are unaware of a "tool set" to aid them, they never actually put what management "knows" (we call it "tribal knowledge") about how their organization works -- or doesn't work -- on paper. Therefore, in the absence of such a written document, the managers themselves cannot read and re-read their own logic about cause-and-effect relationships that flow throughout their enterprise.

Our mind makes thousands of assumptions about what we think we know. Our mind processes these assumptions and incoming information so rapidly, we are unable to filter out our incorrect thinking or invalid assumptions adequately. Putting our thoughts down on paper helps us step through the logic that is leading us to certain conclusions.

Equally important, however, is that fact that, if we never get our reasoning down on paper, it is nearly impossible for us to invite others to truly analyze our logic -- to critically review our logic -- in an effort to help us bring about lasting improvement. As a result, not only do we not realize that we have flaws in our thinking about what's happening in our organization, others who might bring beneficial insights to our aid cannot do so because they, too, cannot help us find the flaws in our rationale. This inevitably leads to the fact that these undiscovered flaws in our thinking about how our organization really works -- or does not work -- remain embedded in our decision-making processes.

The good news is that there is an outstanding set of tools that are readily accessible, easily understood, and relatively simple to apply that will help executives and managers lay hold of "tribal knowledge" and reduce it to an understandable framework (or "theory") about how their organizations function in a real and practical way. Others that have applied that tool set have said things like:

• "I have never seen my business so clearly before."
  
  
• "We truly understand our business for the first time."
  
  
• "This process has helped us regain a sense of control over our enterprise."
  
  
• "For the first time in a long time, we are empowered to move proactively toward real, lasting improvement."
  
  
• "We now have a consistent framework for diagnosing problems and planning for improvement."
  

What is this simple, yet amazing, tool set for executives and managers?

It is simply the TOC (Theory of Constraints) Thinking Processes as developed by Eliyahu Goldratt, a suite of logic trees that provide a simple, yet effective, road map for diagnosis and change.

So, continue to say, "We know!" and miss out on the opportunity for real, practical and sustainable improvements to your enterprise, or discover a whole new, easy-to-use and effective tool set for starting down the road to ongoing improvement.

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Contact me!
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World Class Manufacturing -- Really?

I found this quote on a Web site which will remain unidentified in this article:

World Class Manufacturing - A definition
World Class Manufacturers are those that demonstrate industry best practice. To achieve this companies should attempt to be best in the field at each of the competitive priorities (quality, price, delivery speed, delivery reliability, flexibility and innovation). Organisations should therefore aim to maximise performance in these areas in order to maximise competitiveness. However, as resources are unlikely to allow improvement in all areas, organisations should concentrate on maintaining performance in 'qualifying' factors and improving 'competitive edge' factors.... The priorities will change over time and must therefore be reviewed.

The author here identifies six "priorities":

1. Quality
2. Price
3. Delivery speed
4. Delivery reliability
5. Flexibility
6. Innovation

I would contend, however, that none of these 6 priorities may be achieved without setting the organization's primary focus on making money -- making money both today and in the future. Without making profit the first priority, there is no money to spend on improving quality; there is no money to spend on improving the speed or reliability of delivery; and there is no money to spend on improving flexibility or innovation.

One might say, "Well, if we improve quality, we will make more money." But unless the framework for the planning and focus of the organization has demonstrated by a rational method that improving quality will lead to improved profits, then that statement remains only a "hope" and not a plan or a true "goal." The same may be said for the other five "focus" points in the article.

If the manufacturer has no sound framework by which to determine precisely what steps it must take beginning today to increase its profitability -- to make it more effective at making money -- there is a chance it may not survive long enough to work on any of the six "priorities" listed above.

"Without theory there is no knowing." -- W. Edwards Deming

Having a valid theory -- a consistent "framework" -- by which to evaluate all that transpires within your business is critical to constancy of purpose and effective leadership by management.

Contact me!

(c)2008 Richard D. Cushing

Getting IT right!

Writing in InfoWorld magazine (6 Jan 2003), Ephraim Schwartz said:

"The goal of IT, since its inception, has been the timely (a relative term) delivery of information to those who need it. Behind this goal is an unspoken belief in technology: If IT could deliver to its internal enterprise customers all of the information all of the time, it would be impossible for them to make a mistake."

Understanding the difference between data and information

More likely than not, many of the folks working in your organization's IT department don't actually know the difference between data and information. To be fair, they are not alone: Many people working as supervisors, managers, and executives probably don't recognize the difference between data and information either.

• Data are the bits of information your various systems store. The system may be any kind of system -- not necessarily and IT-related system. Those old metal filing cabinets still found around many offices store data, just like that 160 gigabyte hard-drive on your desktop computer stores data.

• Information is data transformed (e.g., gathered, analyzed, collated, sorted, coded) to allow the user to rapidly digest and comprehend the implications of the underlying data for timely, accurate, and effective decision-making.

For example, a 300-page report printed on green-bar paper, like an old mainframe computer used to spit out for us at a firm I worked at years ago, is data. Make no mistake, the data -- in the 300-page report -- contained everything we needed to know to make an effective decision. However, it its form as a report, it was not readily digested and comprehended for effective decision-making.

At another firm for which I consulted a few years ago, one of the firm's key production managers would take home several reports from their existing system almost every night. Working at home in the evenings, he would comb through these various reports and, using an assortment of colored highlighters, would mark up the reports with various colors to guide his production decisions the following day.

What was he doing? He was transforming data into information.

The data contained in the aforementioned 300-page report could have been more easily digested and decision-making could have been faster and more effective if the data had been presented, perhaps, in a chart, a graph, or even reduced to some form of exception list.

Placing the information in its context

Data content may typically be broken down into three general classes for most organizations:

• Operational data such as orders, purchases, inventory, and so forth;
• Process data such as schedules, routings, bills of material, logistics, and similar; and
• Administrative data including accounting, customer lists, vendor lists, employee lists and more.

The data context, however, must be understood before effective decision-making may be done for any particular organization. The context of the data give the data meaning within the framework where it is to be applied. The context includes such elements as:

• The organization's purpose,
• The organization's strategy,
• The organization's vision and mission,
• The organization's execution model,
• The organization's capabilities and competencies,
• The organization's structure,
• The organization's policies and procedures, and
• The organization's values and culture.

Clearly, depending on an organization's purpose or strategy or production model (for example), essentially the same data may drive two different organizations to make equally effective but totally different decisions.
It should be part of every organization's IT strategy to mandate the transformation of the huge volumes of data being collected into information by their IT systems. This transformation, in itself, should be flexible, timely, and subject to ad hoc transformation, as well.

That's what business intelligence is all about. In today's world, this is all about survival, not just improvement or excellence.

"Business, we know, is now so complex and difficult, the survival of firms so hazardous in an environment increasingly unpredictable, competitive, and fraught with danger, that their continued existence depends on the day-to-day mobilization of every ounce of intelligence."
-- Konosuke Matsushita, founder of Matsushita Electric (Panasonic) as quoted in Managing on the Edge: How Successful Companies Use Conflict for Competitive Advantage by Richard Pascale (New York: Simon and Schuster, 1990), p. 51.