The future is not what it used to be

Leo Sadovy
Leo Sadovy|February 15, 2012

Although he later qualified much of what he said with the statement, “I really never said everything I said”, Yogi Berra is also well known for his famous phrase, “Prediction is very hard, especially about the future”. In an attempt to make Yogi’s dilemma slightly more manageable, three of my SAS colleagues, Lou Galway, David Pope and Robert Szczerba, are being awarded a patent on a process for “Computer-Implemented Systems and Methods for Determining Future Profitability”. I recently sat down with the team to better understand what they are trying to accomplish with this new process, and more importantly, what are the business benefits to be gained from implementing their suggested approach.

In a nutshell, what their process is about is extending the activity-based management approach of determining past profitability at the granular level of the customer or product, into the future, through forecasting techniques at this same, granular level. The value of knowing which of your products or customers are the most and the least profitable, and then taking appropriate action based on segmentation and target marketing, can be readily extended into future-focused actions based on data-driven forecasts. It’s still all about making better decisions, just that now the domain of your decision making time frame has been considerably expanded beyond just the present day.

Briefly, the idea is that just as you can utilize a set of independent variables to forecast most anything: costs, revenues, volumes, you can also utilize an appropriate collection of independent variables to forecast profitability at the very lowest levels. By combining the capabilities of SAS Forecast Server with SAS Profitability Management, what you can get is a forward-looking, pro-forma P&L statement for each of your customers. This is driver-based forecasting not just at the summary general ledger account level, but by customer. It is based on data you likely already possess within the organization, data that until now hasn’t been effectively turned into business intelligence.

This is truly one of those cases where the wizard-driven, automated forecasting capabilities of SAS Forecast Server can immediately be put to effective use, that 80% of the time where the analytical application can automatically create a valid forecast (10% of the time the situation is complex enough to require professional statisticians, and 10% of the time the data is completely random and cannot generate a valid forecast at all). If your financial analysts have had even just one statistics course, and all they can remember is the difference between a dependent and an independent variable, you are in business – the wizard-driven software can do the rest.

The real key to creating business value from such a process comes from integrating your customer demographic and attribute data with your financial data, incorporating the information contained in your CRM, loyalty and marketing management systems with financial cost and revenue data. A couple of examples would be beneficial at this point. For each example below, let’s assume that prior history indicates, by eyeball, on average, simply a flat “trend” line of past purchase behavior.

  • Adding demographic data, such as age, might lead to, say, an upward trending forecast for younger customers and a lower trend for those somewhat older (or visa-versa).
  • Adding attributes, such as the date they joined your frequent buyer’s club, might indicate a future upward trend with a three-month time lag.
  • A purchase history of three or more products from different categories, or one product plus related services, might indicate an upward trend in profitability compared with other buying patterns.
  • Use of coupons, only buying during certain sales events, or only buying after receiving certain target marketing offers could be matched with the planning of such future marketing events to better forecast volumes and production capacity.
  • Perhaps the data shows a switch in buying behavior over time from low-end, low-margin products to higher-end offerings that might portend improved future profitability that is not visible just in the revenue data by itself.
  • An industry attribute, combined with external market or forecast data, might indicate that going forward, customers of the same size and prior buying history may be headed in opposite directions based on their industry affiliation.

There is value in this sort of a granular forecast for both B2B and B2C businesses. In the B2C world, all of the targeted marketing approaches I listed above, combined with some segmentation and up-sell/cross-sell promotions gets you on the right road to be actively managing that elusive concept of customer lifetime value. In the B2B world, imagine if you could use such a process to set quotas and establish territories, by whatever criteria you run your business (i.e. geographic, industry, hunter/farmer, direct/indirect, etc …). Not only can you eliminate arbitrary, one-size-fits-all sales quotas that consistently are points of contention, the software also automatically identifies those outliers, those once-in-a-lifetime $10 million dollar deals that need to be factored into the setting of a proper sales target.

And if that wasn’t enough, there is a next step – optimization and “what-if” scenario analysis. Why? Because you still have constraints, constraints in resources or time or investment, that need to be included in your customer-level planning activities such that it is your most profitable customers and products that get priority.

It was just two weeks ago in my “Finance in more than two dimensions” post that I noted the long-term goal of FP&A to better position itself to engage in more value-add activities tied to business and decision support. While there are many paths one could take on that journey, forecasting profitability at the customer level in support of marketing and account management activities is certainly one path you could readily take using just the data you already have on hand. No, the future isn’t what it used to be, it’s gotten a whole lot better.

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Finance in more than two dimensions

Leo Sadovy
Leo Sadovy|February 1, 2012

I have been attending corporate financial management conferences for 20 years or more now, and there has been one consistent theme that has managed to survive the decades intact: how can finance and its FP&A function become more strategic, more focused on value-add decision support, and less transaction/ journal entry oriented, or as some have said, “we do F & P pretty well, but not very much A”.  I will admit that some progress has been made during this time span.  When it started out the ratio was 80/20 in favor of transactions, with the goal to be able to turn that number on its head, so that it became 80/20 in favor of value-add decision support activities.  The current consensus among FP&A types at the more recent conferences I attend or chair seems to be that we’ve worked ourselves up to a balanced 50/50 split, which means that while we’ve banished Pareto and his 80/20 band of unproductivity thieves from the latter half of the week, we are still stuck with him as a lunch partner through Wednesdays.

Just yesterday at the CFO CPM conference in New York, Mary Driscoll, Senior Research Fellow at APQC, moderated a panel discussion on this very topic entitled: “Profitability Management--How Finance Can Help to Deliver on Strategic Promises”.  In preparing for this panel, I ordered my own thoughts regarding how finance could play a more strategic role within the organization, which I share below, along with some of the additional ideas that surfaced during the discussion.

-   Integrated Business Planning.  Of the strategies that fail, 80% of them fail not because they were wrong, but because of poor execution. The typical 3-level model for IBP usually shows strategy at the top, operations at the bottom, and financial planning in the middle linking the two.  For finance, this is the ideal structure for us to exert influence and control so as to improve those execution odds, starting with assuring that top-level strategy is reflected in the business plan, and continuing the emphasis by also assuring that detailed operational budgets and metrics are linked and aligned with corporate goals.

-   Stratex, or Strategic Expenditure, is a term coined by Robert Kaplan to reflect expenses related to strategic programs and initiatives.  Once again, finance is in an ideal position to assure that strategic projects get their own staffing, budgets and resources, rather than depending on borrowing from benched or excess functional resources who somehow manage to find some cycle time for the project.  Furthermore, finance needs to assure that in difficult times, Stratex is protected from mindless, across-the-board 10% expense cuts.

-   Profitability as a Metric.  Too many organizations treat profitability as a residual, what’s left after expenses are subtracted from revenue.  Without some application of ABM, profitability can only be ascertained and incented at the C-level after all the books have been consolidated.  With ABM, profitability can be driven down to the division, region, department, product or customer level.

-   Risk. Are you incorporating risk into your business decision process, or are you simply going with the largest number, the largest ROI or IRR, the largest “return” irrespective of risk?  If you calculate return to three significant digits, but risk is still just sticking a finger in the air to get an order of magnitude, you are not doing all of your job.  Of the three components of “How Much, How Soon and How Certain” in every business decision, finance is very good at the first two, but typically neglects the associated risk.

-   Cross Functional Coordination. I talked about this one in my recent post, “The Attack of the 50-foot Cliché”. In the absence of a formal Office of Strategy Management, finance is the next most likely function to be in a position to assure that the key, cross-functional processes that create (or destroy) value in an organization are given their proper due; those cross-functional processes that no one person or function owns but that comprise the core of the organization’s value proposition.

-   External factors:  If the finance department is guilty of navel gazing, then most likely the rest of the organization will follow suit.  If the monthly financial reporting package is solely about internal measures and metrics, all neatly packaged in 10K format, then that will become corporate culture.  If instead, the monthly financial reports and dashboard metrics included operational metrics, third-party data, competition, SWOT information, external benchmarks, and if the forecasting process incorporated external sources into its consensus building process, this too would become the new norm, the example to be emulated throughout the company.

-   Business Models:   Once you start incorporating external data, you quite naturally continue to pay attention to the other non-financial external factors that at a minimum affect your business, and may even catch you completely out of sorts with where technology, products, media, regulations, or customer sentiment is taking the market.  I like to think that what Steve Jobs’ genius was about, was in working backwards from a new business model.  He didn’t so much as first invent iTunes and the iPod as he invented a new business model for music distribution – the physical device was secondary.  Same for the iPhone – primarily a piece of technology in support of a new business model for licensable “apps”.  One of the most valuable things finance can do is to get their operational business partners thinking in terms of the business model - how do they make money today, how can that be improved, what external business-model threats loom on the horizon, and what new models might they exploit.

Finance can be quite two-dimensional in its thinking, starting with our VERY two-dimensional spreadsheets.  If we’re going to be more strategic, however, it’s not enough just to think outside of the box, we need to use all the dimensions available to us and start thinking outside the dodecahedron, or outside the hypercube.  Or at the very least, go find yourself a REALLY big (three-dimensional) box.

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Metrics for the subconscious organization

Leo Sadovy
Leo Sadovy|January 17, 2012

Think about what it’s like to learn to ride a bicycle, or play the piano, or hit a fast ball, or to coach a group of middle schoolers to do the same. If asked to explain how you stay balanced on a bicycle, you probably couldn’t do it. If you tried to think about each finger finding the right piano key, you could never play a series of chords let alone an entire song. A fast ball reaches home plate in four-tenths of a second, two-tenths faster than your conscious brain can register it. Yet somehow, you still manage to ride a bike, play the piano, and hit that fast ball, often with considerable skill. What’s going on here?

A new book out by David Eagleman entitled, “Incognito – The Secret Lives of the Brain”, investigates these types of abilities and explains how much, how very, very much of what we do and what we think is managed by subconscious processes completely outside of our conscious control and often beyond our conscious awareness (i.e. temperature control, digestion). It was Freud who first described this “iceberg” of mental processes, with 90% of it below the conscious surface, now further advanced by modern science, which has discovered that your subconscious makes its own decisions several tenths of a second before the conscious mind is aware of that decision. The “you’ of your subjective conscious experience is a minor player when it comes to most of what it is your body does, primarily brought into action only when there is a tie vote or a conflict among your subconscious processes. How do we know this is true, that the brain really works that way? Because you can hit a fast ball. Some part of your brain made the decision to pull the trigger and swing away before your conscious self was made aware of that decision.

The organization you run, manage and lead is a lot like your brain with its autonomous subconscious processes. For the most part, it functions day-after-day, minute-by-minute, without your active control or even your conscious knowledge. R&D adds features, account execs make sales calls, bugs get fixed, equipment gets replaced, customers hit submit online, paychecks get deposited, the lights come on in the morning and the bathrooms are cleaned at night. Don’t call this ‘delegation’, you haven’t delegated anything at this level of detail – this is an organization that has long since learned what to do and pretty much runs itself. If it’s running well it not only doesn’t need you, it doesn’t even care if you are there or not.

But when it does need you, it’s probably crucial. You might only set or change strategy once a year or so, but without adjustments to strategy the organization will just merrily sail itself off towards the edge of the world. And when the problem is big enough that you have to be called in to break the tie or resolve the conflict, it can’t be good news for anyone.

All of this talk about subconscious processes has been a set-up for this question: What is the best way to implement major organizational or strategic change? What is the best way to change a corporate culture before the old one eats your shiny new strategy for breakfast?

The answer is related to how you would teach any complex “organism” a new skill. The early stages are going to require a lot of visible, hands-on leadership from yourself with a focus on the obvious, or as the legendary Vince Lombardi used to start out each summer camp, even with a roster full of veteran players – “Gentlemen, this is a football”. You are going to attach training wheels to the bike, or put a little red sticker on Middle C.

After that, though, you are going to rely on your own body’s, or your student’s body, or your organization’s innate ability to learn by itself. Coaching becomes more nuanced, pointing out the little things, making minor adjustments, trying out variations and interpretations, clarifying the rules. Repetition, repetition, repetition; or, simulation, simulation, simulation (i.e. training exercises).

In the final stage you have backed away even further. It’s now about asking questions and getting the student to question themselves, about encouragement and critique. It’s about game strategy and pre-game preparation and off-season training, situational awareness, developing their baseball or marketing or research IQ. Come game time, once they take the field, they are pretty much on their own, out of your control (I once described my role as an off-season parent coach of my sons’ lacrosse team as someone whose job was to focus them on the task at hand before they took the field to do whatever they were going to do anyhow).

Our final step in this imaginary journey is to establish what sort of feedback would be most appropriate, and if I’ve made my point clearly enough, it should be obvious that the right type of feedback will vary with the learning stage the individual or organization finds themselves. Early on it will undoubtedly appear quite authoritarian and autocratic, disruptive of established norms and accustomed behaviors. As the learning continues the feedback becomes more fine-tuned and focused, and the thresholds/window for acceptable results narrows, corresponding to the standard metrics and KPI’s that we typically employ in performance management.

What about that final stage where the organization is running on autopilot? We too often ignore the information, feedback and metrics that our organization needs at this point. It doesn’t need to be ham-handed or punitive as if there is no trust in our people. The business intelligence, metrics and feedback that the mature organization needs at this stage are what the employees themselves feel they need in order to assess and adjust their own performance, not what we decide we want for the more limited purpose of monitoring. Have you ever considered deploying metrics and feedback that play no part whatsoever in an employee’s or an organization’s performance evaluation?

I’m not advocating abandoning performance monitoring metrics; the captain still needs to know speed, direction, fuel consumption and dangers up ahead. What I am saying is that with so much of your organization running itself without your awareness or involvement, you need to make certain that they are provided with what they need to properly function. It’s no longer about you controlling the organization, it’s about the organization controlling itself in alignment with the big picture strategy you’ve set, communicated, coached and led. It’s about trust.

So where does this leave you, the strategy-setting executive? Free to take your hands off this bicycle and start working on your next big challenge, the next goal, the next transformation, the next strategic direction.

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Black holes and Integrated Business Planning

Leo Sadovy
Leo Sadovy|January 4, 2012

Black holes can be completely defined by just three properties; make that four if you count their blackness. The three properties are mass, electric charge and angular momentum. That’s it. No matter what falls into a black hole, the only quantities and qualities retained are its mass, net charge and spin. Throw in the complete works of Shakespeare or a shovel full of dirt and it’s all the same to the black hole. All the individuality and detail is crushed into oblivion. The black hole simply notes the increase in its mass and carries on doing whatever black holes do.

Does this sound anything like your budget?

Oh, I know, the black hole analogy can be overused at times, but as I noted in my previous post, for every cliché there was a first time, and it was undoubtedly based on some belatedly obvious truth.

As for your budget, you put a lot of time and work into its development, into getting it right, but then pass on a single number, the department or line item value, to the business unit, and it’s as if the detailed planning never happened. The department goes about its business as usual, spending without regard to changes in the underlying corporate strategy that informed the initial financial plan. The “number” comes out of the financial plan and becomes the black hole of some departmental spreadsheet, re-diced, re-sliced, reallocated and reprioritized, no longer aligned with the activities and priorities across the rest of the organization.

This is the disconnect represented by the division between the middle, financial/ functional section and the bottom, operational layer of this Integrated Business Planning (IBP) diagram - between the financial and operational plans. There are two primary approaches to solving this problem: 1) integrated enterprise-class systems, and, 2) integrated operational planning and supplemental schedules.

I recently became acquainted with the first approach, integrated systems, while getting up to speed on the capabilities of SAS’ recent acquisition of Assetlink for integrated marketing management. Too often a carefully crafted marketing spend plan resides on a spreadsheet outside the financial systems, such that actual spending cannot be matched with the budget; the budget, organized by G/L account , does not match the structure of the marketing campaigns; and committed-but-not-spent funds cannot be tracked and reconciled between the two systems. Integrating the two solves most of these issues, while assuring that top-level marketing plans are not ignored by having someone lump everything together on their personal black hole of a spreadsheet and then reallocate based on their personal preferences.

The other approach, integrated operational planning and supplemental schedules, is a capability already built into SAS Financial Management. Here, you can build out, in a spreadsheet-like approach, all of the details you need to plan at the SKU, employee, store, product, part number, project or asset tag level, feed them directly into the summary G/L account, yet keep them separate and secure INSIDE the financial application.  This approach directly aligns the operational budgets for R&D, production, marketing, sales and service with the strategy-driven financial plan.

That bottom half financial-to-operational planning link is probably the easier of the two disconnects to address. The more difficult challenge is between the upper components – strategy and the financial plan. While attending the Palladium Group’s 2011 strategy summit in San Diego last November I had the chance to talk with the Palladium staff about the feasibility of using strategy maps and diagrams as the linking mechanism between that top strategy layer and the financial plans. My conclusion is that such an approach is probably the best mechanism available today for achieving an integrated business plan (financial alignment with strategic objectives) at this level.

Mind you, I’ve made no mention of a balanced scorecard or metrics or KPI’s; those would be after-the-fact measurement and feedback tools. What I am talking about here is up-front alignment and integration, assuring that strategic initiatives and programs are adequately staffed and funded, what Robert Kaplan calls “stratex” for ‘strategic expenditure’.

In my post of November 15 (“I wonder what the king is doing tonight”) I listed the seven CPM best-practices that top organizations are focusing on, with the first two being Integrated Business Planning and Strategy Development. As you can now see, these two are in reality linked with each other, with strategy development not only being valuable in its own right, but a necessary component for achieving IBP. It is by doing strategy development properly, linking the objectives and programs, initiatives and campaigns, directly with the financial plans, and not as merely an afterthought used to justify an arbitrary metrics/ incentive scheme, that you avoid the bottom two-thirds of this diagram becoming a black hole that both eats strategy for breakfast and simultaneously turns it into an unrecognizable mess/ mass.

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Attack of the 50 foot Cliché!

Leo Sadovy
Leo Sadovy|December 13, 2011

The role of the CIO is changing. Or was that the CFO? The CEO maybe? Somebody's role is changing, that much I do know.

How many times have you read just such an opening statement in an article or white paper and muttered “duh?” to yourself before moving on to something less banal? Really, I am truly sorry to have to do this to you, but I’ve recently come across a cliché that is actually in danger of being correct. The role of the CIO is in fact changing, in ways that will shake up every organization on the planet. Finally.

I’m preparing for a panel discussion on the question of how to justify ROI in information technology, and after battling with the related clichés, I’ve decided to chuck them all and propose a more radical response: There is no way to justify investment in information technology in isolation because that is asking the wrong question. The right questions are around processes; holistic processes that include IT as integral to the process and its overall ROI, not as a stand-alone component. There are no longer any IT projects, only business process projects. Furthermore, the questions to ask regarding IT ROI should be about more than just the financial justification, they should be about the relationship and contribution of the process to the organization’s strategic goals. (for a more in-depth insight into this issue, please see the chapter on “Leveraging Technology – IT ROI: An Oxymoron”, p217, in David Axson’s brilliant book, “The Management Mythbuster”)

There was a time when perhaps it made sense to focus specifically on the ROI for stand-alone IT, but that thirty-some year run, beginning with the introduction of the IBM System 360 in the mid 60’s, came to a close over a decade ago with the demise of the data entry department. We have been operating in a transitional period since then, as the Internet has matured, and as W.Brian Arthur discussed in the article I referenced in a post a couple of weeks back, “The Second Economy”, information technology has evolved into the neural network underlying the more obvious and well-known physical economy.

There are no significant processes any more that can be considered without including their associated IT as an integral part of that process. Airline reservations without IT? Customer service without IT? The financial close without an IT-based financial system?  Nowadays airplanes land themselves, cars park themselves, and the Space Shuttle could not be manually controlled until near the very end of its landing approach when its airspeed drops below the speed of sound – above that speed humans cannot react quickly enough to the required changes in wing dynamics. Unless you were a clerk yourself, can you even remember how McDonalds took and managed your order before the advent of touchscreen terminals?

It simply no longer makes sense to talk about the IT separately from the process it enables. As I have previously mentioned (here, and here), it is in the processes where value is created or destroyed in an organization. Taking Arthur’s ‘neural network’ analogy one step further, it would make no sense to debate the value of the nervous system separately from the value of the muscular or gastro-intestinal systems. What might make sense, however, would be a discussion of the right type of nervous/IT technology to deploy in support of the processes of bodily movement/integrated marketing management: autonomic, sympathetic or hormonal / master data management, BI and analytics.

Today we have matrix management in many organizations, with the matrix being between support and line/operational functions. The future will see the continuation of matrix management, but with the matrix instead being between the processes and the functions. Entities will organize themselves around their key processes. Business schools will offer degrees with concentrations in a functional domain (as they do today) and one or more processes. Bill McCracken, CEO of CA Technologies states that we’ll be talking about the CIO as the BIO – business information officer.

I’m going to call his BIO and raise him an SPO – strategic process officer. A key point of discussion at last month’s Kaplan and Norton Palladium conference in San Diego was: Where is the best home for strategic cross-functional processes? Those key cross-functional processes that no single function owns in its entirety. Their conclusion was that these need to be coordinated by an Office of Strategy Management (OSM) reporting into the CEO. Again, I am going to raise their OSM by predicting that the business entity of the future will be primarily organized around its key process (or groups of related processes) that support the vision and mission of the organization. Instead of functionally oriented VP’s for R&D, Marketing and Production, there will be VP’s for Innovation, for Customer Relationships and Satisfaction, and for Quality and Order Fulfillment. There will still be the need for domain experts in marketing, finance, engineering, analytics, and so forth, but these will be subordinate to the value-creation process, perhaps with a director of IT reporting to each of these process owners, advising them on the best information technology to apply to the process given its strategic goals and improvement objectives.

There may still be an OSM, but instead of trying to coordinate the several aspects of, say, a customer service process into and across functions, its job will be to link, coordinate and align the organization’s key processes – a much more worthy and valuable objective.

Is there any evidence of this pending change? I believe there is. In conference after conference, in the business case presentations, I have been seeing one half of this transition for some time now – the focus on process, especially for those organization who have a customer-centered mission or vision (as opposed to those focusing on innovation, quality or low-cost production). A recent example was Cisco’s presentation at the Palladium conference, where not only was their starting point the customer, but the entire order fulfillment process centered on the customer, with the customer located at the START of the process chain, not at the end. While the process elements are still supported functionally, it is only a matter of time before leadership recognizes the need to shift management from a functional to a process focus.

So, is the role of the CIO changing? You bet it is. Today’s CIO is stuck in a no-man’s land, between technology, and the business processes that information technology enables. Those with a more technical bent will find a home advising and implementing information technology on behalf of the business process owner. Those who want a more strategic role will evolve, as Bill McCracken suggests,  into business / operational leaders who understand how their chosen process creates value and how technology can make that process more efficient, effective and competitive. They will still need to justify their planned investments, but the ROI will be a function of the entire process they manage, not just the IT component. And increasingly, that ROI will be measured not only in dollars and cents, but also as it contributes to the mission, the vision and to the strategic goals of the organization.

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Rolling forecasts, or Who ordered that?

Leo Sadovy
Leo Sadovy|November 29, 2011

I have previously dealt independently with issues of forecasting, planning, and budgeting in separate posts, and the time has now come to pull them all together in one place and just come out and say what I really mean. This integrative post was prompted by a recent invitation I received to address the topic of the benefits of rolling forecasts, where my starting point is always the wise words of David Axson, who said, if you’ve got problems with your forecast process or accuracy, you are not going to fix them by simply multiplying and repeating the same process on a regular, rolling basis. If you work backwards from what it is you want to achieve, very seldom will ‘rolling forecasts’ be the answer. Or, in the words of physicist Issac Rabi (when informed about the discovery of the muon): "Who ordered that?"

First, let’s recap the terminology:

- TARGETS: What you’d like to happen
- FORECAST: What you think will happen
- PLANS: What you intend to do

… and perhaps most importantly,

- BUDGETS: How you are going to allocate your resources.

Because of the now obvious imperative to maintain an agile approach to planning and execution, I am most adamant in my restrictive definition of ‘budget’. Budgets are not to be used for cash planning, targets and incentives, investments, or cost understanding; there are other, better systems for this, and forcing budgets into double, triple or quadruple duty seriously cripples their resource allocation function during volatile times.

With that in mind, I once again reiterate the proper relationship between strategy, planning, forecasts and budgets. Planning is the central component, informed by strategy and forecasts, with the budget(s) as the primary output.

Scenario planning for most-likely, optimistic, pessimistic, best and worst cases, is composed of the following key components:

- The definition and description; of the scenario itself, sufficiently developed so that everyone can recognize it when it occurs and can easily rule out any near misses that it might be confused with.
- The budget; the reallocation of resources or priorities, associated with the scenario.
- The trigger; what measurable quantity must attain to engage the new scenario.
- The implementation plan; is it all or nothing/ all at once, or are there logical stages or steps.
- The incentives; the management bonus schemes and metrics that replace the old regime and will now reinforce the new behaviors.

When it comes to traditional budgeting, we seem to gravitate to one most un-agile technique that I liken to laying 12 months of railroad track at a time, with the only option when conditions change being to issue freezes: hiring freezes, salary freezes, capital freezes and travel freezes, that please no one, not even the CFO who issues them. And how often has your organization gotten to January without a budget in place, with no railroad track at all? On the other hand, we can’t let the organization run around on ATV’s completely unencumbered from fiduciary governance or unaccountable to changing strategic priorities.

The answer is to lay only as much railroad track as each function requires, which will almost never match up precisely with the 12-month Gregorian calendar (in fact it would be a good idea to purposefully avoid 12-month budgets of any kind, even if the project so indicates, make it 11 or 13 months instead). Capital investments and long-term projects will require a budget allocated through to completion, be that six months, 18 months or five years. Programs, initiatives and campaigns, in support of strategic corporate priorities such as quality, customer satisfaction or innovation, need their own budgets so that they are not relegated to operating in cycle time, borrowing resources from traditional departments, and being treated as step children when instead their resource allocation should reflect their strategic importance to the organization (a formalization that Robert Kaplan calls “Stratex” for 'Strategic Expenditure').

When it comes to departmental budgets, scope is still important. Marketing probably needs the ability to commit resources at least a year out for future events and trade shows, whereas sales or production might be kept on a shorter leash more in step with market ups and downs. Neither do sales quotas need to be twelve months in length either – match them instead with the natural sales cycle of the product or service, be that three months or eighteen; it will do wonders to ameliorate one of our biggest self-inflicted wounds – the year end hockey stick.

If your budgeting process is to meet the ‘agility’ criteria, the first thing you want to decouple from the budget are targets and incentives. You cannot be an agile organization, reacting quickly to opportunities and challenges, if in order to implement a revised budget you must also renegotiate the associated bonus schemes at all levels. Targets and incentives are best managed through the use of a Balanced Scorecard, where they can be tied to inter-related key metrics and to external benchmarks such as growth and market share that better reflect the health and performance of the organization than simply an internal, departmental budget.

Finally, it must be recognized that different forecast sources are better suited at providing data for different time horizons than others. Point of sale and ERP systems are most valuable in the shorter daily-weekly-monthly time frame, whereas field sales and departmental expense forecasts can reasonably extend out nine months, and with marketing, industry, government and third party forecasts relevant in the 1-to-2 year horizon.

The point here is that in this context it makes no sense talking about a ‘rolling forecast’. Forecasting is a continuous process that collects, integrates, processes and incorporates into the planning process the most relevant data from each separate forecast source appropriate to its applicable time horizon. Forecasts – plural - as the enterprise seeks to gain as much information, insight and foresight from as many sources and time horizons as seem reasonable. You don’t force an ERP system into provide a rolling 18-month view when backlog only goes out 3-6 months, or when sales can only be accurate out to nine months, and you don’t ask marketing what sales will be next quarter, you ask them instead how product launches, retirements and migrations will affect revenues a year from now. You most certainly do not want to create and encourage an environment where people simply make up the numbers to fulfill corporate’s arbitrary “18-month” rolling forecast mandate. And furthermore, you don’t want to operate in knee-jerk fashion every time there is some change in one particular forecast source, or rely on just one primary forecast input – you integrate them all into one consolidated, weighted forecast view that collectively informs a continuous planning process.

It is the PLANNING process that is rolling and continuous as new information becomes available. An 18-month planning view makes sense - an 18-month forecast from each and every source does not. Scenarios are developed, extended, amended, updated, discarded, and/or modeled as new forecast data warrants and as strategy directs. Resources are then allocated to the functional departments based on the plan on an ‘as-needed’ basis, with some functions requiring longer lengths of bite-sized chunks of railroad track than others depending on the appetite of the resource consumer and upon changing financial, market and/or economic conditions. When you start with better decision making, which includes better resource allocation, as the goal, rolling forecasts do not emerge as the mechanism, but a rolling, continuous scenario planning approach does.

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I wonder what the king is doing tonight

Leo Sadovy
Leo Sadovy|November 15, 2011

Yes, that’s me, as Don Quixote, singing ‘Dulcinea’ from’ Man of La Mancha’ in a Broadway-themed variety show benefit concert (sort of like "Glee" for forty-to-fifty-somethings) raising money for anti-malaria netting in Africa (I did this as a medley along with ‘I, Don Quixote’). The total amount raised was over $20,000 (including a donation from SAS), which will buy about 2,000 nets. Undoubtedly the heaviest Don Quixote you will ever see; looks more like Sancho Panza to tell the truth, but it was a low-budget production and I was the best they could get.

Originally I was going to do a medley from some of the great Broadway shows of the early 60’s – Camelot, My Fair Lady, West Side Story and Man of La Mancha, but the director wanted me in costume, so I had to stick with one show and one role. Still, my mind has recently been on the songs from these other shows, Camelot in particular, which provided the inspiration and title for this week’s post.

Gartner has their five stages of maturity for Corporate Performance Management (CPM):
1) Unaware
2) Opportunistic
3) Standardization
4) Enterprise
5) Transformative …

 

… and at SAS we use the acronym SMILE to illustrate the evolving nature of the use of analytics in CPM:
1) See
2) Manage
3) Improve
4) Learn
5) Evolve

Either way you cut it, most organizations, 85% or so, find themselves in one of the first three Gartner stages or the first two levels of SMILE, struggling to simply See “one version of the truth”, understand cost and profitability at the product and customer level, and then use that data for the basic Management of the firm. That they find themselves in this position is not always due to poor financial management, often it’s the result of mergers and acquisitions that set a company that was making good progress back to square one on the learning curve as they digest and integrate yet another new business. In other cases the business is in high growth mode with finance laboring valiantly to keep up with the increasing volume and complexity.

While we may find ourselves mired in the tribulations of our day-to-day functions and objectives, most of us have higher aspirations, for ourselves and our organizations. All of the conferences I chair and attend are focused on improving the FP&A function, on piecing together the components of a greater vision for the finance organization. And when I present to clients myself, the question I am most often asked is, “What are the best practices, what are the top 15% doing”? After I’ve got my budget season under 90 days, or my close down to 3 days, or implemented rolling forecasts, activity-based costing, detailed operational planning, dashboards, KPI’s and a balanced scorecard (BSC), what’s next? Or, to phrase it musically, What IS the king doing tonight? And as Richard Burton responded,” I’ll tell you what the king is doing tonight (he’s wishing he were in Scotland, fishing, tonight”):

1) Integrated Business Planning: Linking strategy to financial plans, then linking those with S&OP and marketing/capital spend (hint: consider using the BSC and strategy maps as the bridge).

2) Strategy Development:  You began in the middle, with KPI’s and a scorecard, now you want to go back and link those with strategic goals and objectives, where you should have started in the first place.

3) Risk Management:  When it comes to analyzing the risk/reward equation, we’re quite good at the reward part, with NPV and IRR and TCO, but often have no idea how to assess the associated risk (see my “How Much, How Soon, How Certain” post)

4) Cost and Profitability Optimization: Knowing your cost and profitability at the product and customer level is a great first step, now you need to put that valuable information to use, applying it to marketing and customer relationship decisions, to production and quality and market mix decisions, and to activity-based budgeting where you plan for capacity and resources based on forecasted outcomes.

5) Analytical Forecasting: Driver-based budgeting and forecasting, for greater accuracy, faster scenario plan devleopment, more detailed forecasts available more quickly with fewer resources.

6) Scenario Planning: If we learned only one thing out of the global economic calamity of 2008-09 it was that we need agility in our financial and business planning process. Budgets can become obsolete before they’re even rolled out, and laying 12 months of budget railroad track is no way to be agile in today’s economic environment; not only do you need Plans “B” and “C”, but up also may need a Plan “V”. (stay tuned for NEXT WEEK's POST! - I'd provide a link to the future if it were possible).

7) Closed-loop Performance Management: The upward-trending “Information-to-Insight” arrow is only half the story. Best practice is to feed your performance metrics back into strategy formulation and adjustment, and into scenario planning and resource allocation.

This is what the king is doing tonight - the list of what the top companies are focusing on in their pursuit of financial and operational excellence. These are the performance management best practice objectives of the best organizations. This is the vision that SAS envisions for you.

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Normal accidents, Risk, and the Man who Saved the World

Leo Sadovy
Leo Sadovy|November 1, 2011

If you are feeling out of sorts, a bit down and out, and want to take it all the way to full-blown depression, have I got a book recommendation for you: “Normal Accidents”, by Charles Perrow (1984). Perrow’s premise is that we have designed certain systems, nuclear reactors being his primary example, that are so complex that they are prone to the unanticipated interaction of multiple failures. Perrow’s definition, also called ‘system accidents’, consists of the system having two main characteristics: interactive complexity and tight coupling, and these systems can be either technological or organizational.

The first part of the definition, interactive complexity, is simply where the system has too many combinations and permutations of configurations to effectively model them all in advance. How a failure at one step can affect operations at another downstream can sometimes be modeled correctly, but introducing a third failure and predicting how all three will interact is often unknowable in practice.

Tight coupling means that A-causes-B-causes-C-causes-D is a given – the system is designed on purpose to automatically execute a certain chain of events once the initial conditions at step "A" are met, and another chain of events for a different set of initial conditions. There are no “loose” couplings where perhaps there is human intervention or where the system waits for confirmation from an independent source.

Normal accidents are at the extreme end of the risk we all manage for our organizations as a matter of course. Robert Kaplan (of Balanced Scorecard fame) defines three major categories of risks. Category I risks are those known-known risks for which we get no benefit, such as fraud, theft, or embezzlement, where the objective is to minimize or eliminate the risk. The perpetrators of fraud are typically engaged in behaviors that readily surface through pattern recognition analytics, and if they don’t change their pattern quickly enough, they can and will be caught. Fraud is currently the number one search topic on SAS’ websites, as organizations look for ways to minimize the cost of these Category I risks.

Category II risks are those where the risk-reward equation comes into play: yes, the risks are there, but so are the benefits, so are the rewards, if the risks can be properly managed. These are the business or operational risks that I have addressed in some of my previous posts, such as “How Much, How Soon and How Certain”.


Category II risks have three components: Level of risk, level of importance, and core competency. On the accompanying graphic, risk is represented by the vertical axis, importance by the darker colored bars (1, 3 and 4) and core competency by the solid fill (1, 2, 3 and 6), with 4 and 5 being two functions which the organization does not feel they have core competencies in.

Before we get back to what to do with this information, let’s dispense with the definition of Kaplan’s Category III risks, those unknown-unknowns such as earthquakes and revolutions for which, like Category I, there are no associated benefits, but are by their nature, unpredictable (I have dealt with these in earlier posts, such as “Black Swans” and “Plan V”, where scenario planning becomes the key risk mitigator).

The whole point of investing for a return on that investment is that there are high-risk opportunities out there which are both important and in which you have a core competency. While a few of the component combinations might be straight forward, most will require analysis and deliberation before coming to a conclusion regarding the best approach. For certain obvious areas where the risk is high and the competency low the risk mitigation strategy will likely involve outsourcing and/or hedging. Outsourcing a low importance function like office supplies can be a simple direct buyer/seller arrangement with a vendor (no company ever went bankrupt over yellow highlighters and copy machine paper), while the outsourcing of something more important, like IT, will require a more complex, on-going business arrangement.

In this example, function 5 might be a good candidate for outsourcing to a vendor – medium risk, no competency, and not terribly important. Function 4 is a more difficult situation – high risk, no competency and highly important. Outsourcing might be an initial good first step, with the intent to acquire core competency and bring it back in house at a later date, perhaps swapping resources with function 6, which is both less important but holds more risk. Functions 1, 2 and 6 will all generate interesting internal analysis and discussions regarding hedging strategies, perhaps warranted by the higher risks in 2 and 6, and the greater importance attached to #1.

One last lesson that can be learned from this deliberately ambiguous example is that, as a commercial enterprise, this organization is at great risk of becoming irrelevant in its chosen market. Such an analysis shows that the company has no function where it displays a core competency in an important, high-risk capability. It’s not tackling any hard problems and most likely not adding much value for its customers. No risk, no reward. Time to rethink strategy I would say.

As valuable as this approach is, it still can’t tell you if your business processes are prone to becoming a ‘normal accident” or not. Most organizations are sophisticated enough to conduct this type of point-by-point, function-by-function, capability-by-capability analysis and make decent business decisions. And most are in a position to model their basic processes for high probability single points of failure. Given that you’ve not made your processes more complex than absolutely necessary, Perrow offers only one other way out of normal accidents – loosely couple your processes.

Which brings me to The Man who Saved the World, Stanislav Petrov. In my humble opinion, the Nobel Peace Prize committee can save itself a lot of time by just naming Petrov as next year’s recipient. You can Google “The man who saved the world” to check out the details, but the short version is that on September 26, 1983, lieutenant colonel Petrov of the Soviet Air Defense Forces correctly identified a missile attack warning as a false alarm, a decision that may have prevented an erroneous retaliatory nuclear attack on the United States and its Western allies. Investigation of the satellite warning system later confirmed that the system had indeed malfunctioned and it was subsequently determined that the false alarms had been created by a rare alignment of sunlight on high-altitude clouds and the satellites' orbits, an error later corrected by cross-referencing a geostationary satellite. Talk about “system accidents” – that would have been a big one. Petrov was the loosely-couple component of this complex system, and he played his role perfectly.

As wonderful as it may seem to see your operational processes humming along smoothly all under computer control (see last week’s post on the “neural network” of the economy), proper governance and regular human monitoring of your business processes is the best way to avoid your own version of the “normal accident”.

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Encountering analytics

Leo Sadovy
Leo Sadovy|October 19, 2011

In his recent article for the McKinsey Quarterly, entitled “The Second Economy”, W. Brian Arthur of the Santa Fe Institute states, “In any deep transformation, industries do not so much adopt the new body of technology as encounter it, and as they do they create new ways to profit from its possibilities.” As we speak, industries are encountering, and have been encountering, the ‘Second Economy’ of analytics for some time, and have in fact found a myriad of ways to profit from its adoption. With respect to Arthur’s ‘Second Economy’ theme, analytics creates profitable opportunities through improved decision making in two ways; insight, and automated decision making.

While I consider the full article a must read, a quick synopsis of Arthur’s primary premise is that a second, digital economy is developing and growing underneath the physical economy of goods and services that we are most familiar with, and that this digital economy will transform society more dramatically than any previous technology. Just as steam, gasoline, electric and nuclear power came to supplement and in many cases replace human labor in the physical economy, information technology is augmenting human brain power, and again, in many cases, replacing it completely. That computers have better memories, more storage, and can calculate error-free faster than humans is now a given, but what is new is how IT is replacing direct human intelligence in large portions of the business process value chain. As an example, think of how automated air travel has become, from reservations to check-in to baggage handling to security to things you don’t even see, like aircraft weight distribution and fuel requirements.

The digital transformation of the second economy comes not just from replacing physical human activity in the business processes (think ‘travel agents’), but more significantly, how it is augmenting and even replacing human decision making.

The augmentation of human decision making for insight arises from several analytically-driven areas:

- Short-term and high-volume forecasting can be done with greater accuracy.
- Likely customers can be targeted for specials, cross-selling and up-selling.
- Production, service and operational processes can be optimized.
- Most and least profitable customers and products can be segmented for action.
- Risk can be quantified and managed.
- Text analytics can ferret out customer sentiment.
- Strategic objectives and KPI’s can be validated against expected results.

The common thread running through the above is that analytics removes much of guesswork. Fact-based decisions replace seat-of-the-pants gut instinct and intuition.

But if that was all there was to it, it wouldn’t warrant a claim to be a significant part of the future Arthur sees for the Second Economy. Instead, information technology and analytics is not just augmenting decision making, but in many cases, is replacing it altogether, in real time. Analytics for real time decision making is becoming embedded in the digitized business processes themselves, where the second economy directly affects the physical economy without the intervention of humans. Consider:

-  Program trading on Wall Street.
-  Credit card fraud detected, accounts frozen and people alerted.
- Revenue and pricing optimization for perishable inventory (i.e. hotel rooms, airplane seats)
- Quality control feedback loops in production processes.
-  Point-of-sale discounts and coupons.

As with the previous list, there is a common thread to this one as well, a thread that Arthur identifies as the ‘neural system for the economy’ - the digitized Second Economy “constitutes a neural layer for the physical economy”. And like any proper biology metaphor, this one can be authentically extended to the concept of learning – these analytical processes LEARN and perform better and better as they gain more experience with both the physical economy and the other neural components of the Second Economy that they interact with.

These lists are only going to grow longer as more aspects of more industries ‘encounter’ analytics and create for themselves new ways to put them to use to augment and replace real time human decision making. The above examples tend towards the single case of analytics embedded within the process, but the future will see analytics increasingly embedded at the point-of-inquiry / point-of-sale, and even earlier, at the point-of-decision. Putting analytics to profitable use is limited only by that oh, so very human capacity for creativity and the imagination to see the possibilities.

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Know when to hold them, know when to fold them.

Leo Sadovy
Leo Sadovy|October 12, 2011

Buy low, sell high. We have all heard this one piece of can’t miss investment advice, but few of us can execute that simply strategy consistently. The difference, it turns out, between the pros and the amateurs, is predominantly about just one side of that equation, the sell side. Most people can and do “buy low”, that seems to be the easy part, but while we we’re hanging on to the hope of further gains, the pros have already sold and moved on. They have successfully executed on that crucial “sell high” component, leaving the amateurs to their buy low, sell low pattern of mediocrity. If you watch any of the televised poker that seems to dominate every third cable channel, notice that the pros play very few hands beyond their initial ante, and that laying down a losing hand comes so much easier to them than to the delusional amateurs who are instead picturing big winnings if that flush draw comes through.

The same holds in the business world. Knowing when to sell, when to move on, when to retire the product or kill the brand or stop the bleeding. “Who is the best owner of your assets?”, the key question that successful business face, analyze and answer, but which the less successful ones put off or ignore until they find themselves not just selling low, but selling lower. Depending on where in the product life cycle your offering sits and on your core competencies, you may not be the best owner of your assets.

As Geoffrey Moore, the well-known high-tech consultant and author of “Crossing the Chasm”, describes in his book, “Dealing with Darwin”, different strategies, management skills and core competencies are needed as a product moves through its life cycle. Some companies manage this transition admirably, some with difficulty, some cannot successfully manage the key transitions at all (i.e. from introduction-to-maturity, or from maturity-to-end-of-life), and some don’t have the core competencies to handle certain components of the cycle, such as innovation, or high volume production. Perhaps they were the best owners of their IPR when they created and introduced the product to the early adopters, but should have sold it off once it hit high volume sales. Or, they can manage through the fat part of the life cycle efficiently, but cling to end-of-life products too long, “zombie products” I have heard them called, incurring high cost to serve and stifling innovation out of a fear of cannibalizing their former mainstream offerings.

One company that knows how to execute Moore’s Innovation Cycle with a “sell high” strategy is 3M, the $26 billion dollar manufacturer of instantly recognizable household brands such as Scotch, Post-It and O-Cel-O, and the maker of industrial adhesives, packaging and health care products. 3M, consistently profitable, even through the recent economic crisis, calls itself “fundamentally a science-based company”, and focuses on innovation and the imaginative application of its technology competencies. But more than just science , 3M has the wherewithal to manage its thousands of new products through the stages of the product lifecycle, including that key last stage, closing it down and reallocating those resources back to where they can be more productively employed. It can typically be said of 3M that half of its products are new within the last five years, which implies that they know what to do with the old ones. They know when to fold ‘em. And they do this, of course, without resorting to massive layoffs every time a product reaches end-of-life; their 80,000 employees are constantly engaged in the processes of moving each successive batch of products through the life cycle.

Which brings me back to you and your business and your products. Do you know when to fold them? Or do you hang on well past the sell-by date, hoping for turnarounds that never materialize? While I suspect that wishful thinking accounts for much of the unfortunate ‘sell low’ results, I put most of the blame on a lack of planning and a lack of facing the reality of product life cycles up front. Our business plans simply refuse to contemplate the inevitable. They continue to project upward linear growth even after the downturn has become obvious to all.

Sometimes it is because we have, in an ill-advised, unbusiness-like manner, left the original inventor/innovator in charge of the product all the way through its lifetime, an initial owner who has too much time and ego invested in the product to properly face the music and manage its eventual demise. Or we leave it with an innovator who simply lacks the process management skills it takes to extract value as the product matures.

Whatever the proximal reason, the root cause most certainly goes back to a lack of proper business and financial planning. A lack of independent forecasting. A lack of developing an initial business-case scenario that reflects the full life cycle. There is no reason not to take advantage of the operational planning capability in your financial software to develope a portfolio revenue projection at the product level as each new product is introduced. If nothing else, it will keep you honest about revenue forecasts and remind you to continually ask yourself if you are still the best owner of that asset. It will force you to develop, at the onset, a plan for product retirement, be that a sale to a channel partner or killing it off completely. Knowing when to fold ‘em is absolutely critical if you are not going to destroy all the value and profit you created during the product’s lifetime by hanging on too long and selling low, low, lower.

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