Map Rock Problem Statement – Part 2 of 5

This is Part 2 of 5 of the Map Rock Problem Statement. After a discussion on how I decided to develop Map Rock in, Map Rock Problem Statement – Part 1 of 5, Part 2 describes the target audience as well as the primary scenario for this Version 1.

Map Rock’s Target Audience

Map Rock’s target audience are those held accountable for meeting objectives in an ambiguously defined manner. Their objectives are ambiguous in that there isn’t a clear path to success and thus there is an art to meeting their objectives. This traditionally includes the managers; the CEOs through middle managers to team leaders. But it’s crucial to point out that even if you are one of the guys with no direct reports, as a modern, commando-like information worker, you still have a growing level of responsibility for designing how you achieve your objectives.  Map Rock is a software application intended to help such information workers through the strategy invention process and the execution of that strategy.

Map Rock isn’t just a “high-end tool” limited to a niche audience of quants, wonks, and power-users all with highly-targeted needs. For example, I’m aware of some of the marketing problems associated with the abrupt dropping of the PerformancePoint Server Planning application back in 2009. It was a very complex tool for a very small audience of managers. Such a product may not be a good fit for a Microsoft that develops blockbuster software for a wide audience (“whatever for the masses”), but can be a great opportunity for a startup willing and able to crack a few nuts. However, my goal isn’t to develop and sell a blockbuster software that goes “Gold” or “Platinum”. While financial success is naturally one of my goals, more importantly, I have a vision for BI which include – certainly not limited to – notions such as these: 

  • Assist information workers with finding relationships they don’t already know.
  • Blur and smooth out the rough, abrupt hand-off points between human and machine intelligence.
  • Do better than keep on shoving square pegs into round holes because things need to be neatly categorized.
  • When making a decision, what if I’m wrong and what can I do about it?.
  • Help humans to regain the appreciation for our rather unique quality of imagination and its artful application. (See Note #1 for my comment on “art”.)

The answer isn’t another high-end, power-user tool, or on the other extreme a watered-down, lowest-common-denominator, single-task tool.  I built an integration technology that will tie the efforts of managers, IT, wonks, and commando information workers. Towards that goal, I needed to dive deeper than the planning activity that the PerformancePoint Planning application addressed into the abstract lower-level of strategy, which is an activity common to all people trying to make their way in the world.

I’ve pondered whether Map Rock is a “data scientist’s” tool. I think of a data scientist as someone with the wide-ranging skill required to procure and analyze data. My view of a data scientist is someone with an “A” or “B” (in the context of school grades A through F) level of skill with databases, analytics, and business (all broad categories in themselves). This is different from quants and wonks who generally have a narrower and more focused “A+” level of typically math-oriented skill, utilizing a narrow range of highly specialized tools such as SPSS.

I see the data scientist as the high-end but not exclusive audience of Map Rock. So I need to be clear that Map Rock is intended to work best as a collaborative application, not a single-user, stand-alone tool. As I mentioned above, Map Rock integrates the efforts of human managers, IT, wonks, and commando information workers. The data scientist plays a crucial role in a Map Rock ecosystem but not like a DBA who manages the database system but is not herself a consumer of the data. The data scientists using Map Rock are more in spirit of the entrepreneurs of an economy who keep the economy robust through their push for change and are also consumers themselves. And in some ways like the Six Sigma black belt who actively nurtures the system.

Additionally and equally importantly, Map Rock integrates these human intelligences to the machine intelligence captured in our various BI implementations; Data Warehouses/Marts, OLAP Cubes, Metadata repositories, and Predictive Analytics Models. From this point of view, data scientists are also like the ambassadors of the human world to the machine world, as they speak machine almost as well as they speak human.

At a higher level (the organization level), the target audience also considers the plight of the corporate “Davids” (of David and Goliath fame) who have come to terms with the fact that they will not beat those Goliaths at the very top of their market (ex: McDonalds and Burger King, the Big Three Automakers) by playing their game. Any entity at the top is at the top because current conditions favor them. Those conditions may have been imposed on the world by them a while ago through crafty engineering, it already existed and they saw a way to capitalize on it, or most likely a happy series of events lead to dominance (somebody has to roll heads ten times in a row). In any case, it seemingly makes sense for the members of that “royalty” to do all they can to preserve those conditions, at worst controlling the relentless wave of change as best as they can. They play primarily a defensive game. They have at their disposal the sheer force of their weight, to exploit the powers such as economies of scale, brand name recognition, lobby for laws, trip up the promising startups. This isn’t bad, it makes perfect sense. But eventually, controlling change, plugging one hole leads to two more, then others, until finally, the system explodes or implodes.

The scrappy “sub-royalty” corporations below the royalty of #1 and #2 in their market at the same time keep exerting pressures by finding novel ways to topple #1 and #2; playing a wiry offensive game capitalizing on the virtues of being small. They find their weak spots and hit the Goliath there. This audience is the one that would have incentive to take Performance Management to the next step, beyond a “nervous system” to a focus on strategy.

Just as compelling are the thousands of relatively small”conglomerate” corporations consisting of a number of franchises such as hotels, fast food restaurants, and medical practices. These mini-businesses, for which there could be a few to hundreds in the conglomerate, span a range of markets and localities meaning each piece involves unique characteristics rendering what works one place useless in another. For example, it would be very useful to be able to test the risk of applying an initiative that worked in a pilot project across the board to all medical practices.

The most common negative feedback I get on Map Rock is some form of, “People would not want to do that.” That is, they will choose to rely on their gut instincts as opposed to turning to a software application to validate their beliefs, to find new levers of innovation, to explore for unintended consequences, to clarify a mess of data points back into a coherent picture. Curiously, most of the people who tell me this are themselves the player/managers I will talk about more below. Remember, Map Rock in great part about blurring the line between human gut instincts and the cold hard facts of our BI assets, meaning things don’t need to be “this or that”.

Yes, Map Rock goes beyond a tip calculator or the sort of “there is an app for that” software. While it is painful to learn anything new, enough incentive can get us to do all sorts of things. In other words, the pain of learning is less than (actually much less than) another pain the learning is attempting to resolve. The incentive here is to win. Corporate entities don’t exist simply so we have somewhere to do things. Map Rock is about enhancing the abilities of information workers, which is beyond just speeding up a process to get the work done faster to make room for other work (or even play). So I ask:

  • Are you willing to limit your options to only what you know? Are you going to limit yourself to that closed box which you may have mined to death over the years, depending solely on the existence of some gem you have yet to find?
  • Even if you feel confident in your knowledge, say from being in that position for decades, are you really sure that you know everything about your job? There is nothing else to learn? Are you 100% confident you kept up with the changes? Your mastery at your position hasn’t blinded you from things going on outside? Are you confident you’ll always stay in that job, never needing to take a few steps back in the mastery of your subject area?
  • Your actions don’t exist in a vacuum. Do you know how your actions affect other departments? Inadvertently, or even knowingly – like when there is so much going on and a deadline is looming, we realize we can’t save everyone. On the other side of the coin, at the risk of sounding cynical, are you certain all of the other managers will not jump on an opportunity to excel, even at your expense?

One version of the “people aren’t going to do that” I’ve heard a few times is the notion that people only want to do the least amount possible to accomplish their tasks. The reasoning is that our plates are already so full there is just no room for anything else, there isn’t enough time to even take care of what is already on our plates. While this may make logical “business sense” from a common-sense point of view, I find that very sad and a bit insulting to the many who consistently go beyond the call of duty, not just at work, but in many facets of their lives. While it may be true that many people would not want to think more than they need to and do the least amount possible to satisfy their most obligations, when it comes to one’s livelihood, I would think that is incentive enough to buck up and fight.

Perhaps you feel you are in a job where you think you aren’t paid to strategize (one of those “We don’t pay you to think” jobs), you’re paid to simply execute instructions as flawlessly as is humanly possible.  I’m not sure how comfortable I’d feel if I consider the implications of what the consistent improvement of Artificial Intelligence and robots hold in store for the value of such roles. That is, especially after conversations with an old auto worker comparing the assembly lines of the 1960s to the assembly lines of today. If outsourcing jobs to countries with low wages seem bad, think about outsourcing to a robot that doesn’t complain and can do your job flawlessly. See Note #2 on Robots.

Business Problem Scenario

At most feisty corporations, meaning those that are playing to win (as opposed to “not lose”), a periodic (at least annually, but to lesser intensities, quarterly or even monthly) ritual takes place called the Performance Review. Every employee, both managers and worker bees, are evaluated on their performance during the previous period and assigned targets for the next period. Those targets originated from corporate goals and high-level strategies designed by the corporate generals to meet those devised goals, and then trickled down the org chart. As the high-level goals and strategy trickle down to wider and wider breadths of people with increasingly specialized roles, they receive increasingly specific goals and objectives.

That trickling down goes something like this. A CEO deems that we must focus on our ability to retain customers and devises a strategy to “delight customers”. The VPs are given objectives specific to their department. For example, the VP of Manufacturing works to improve quality to Six Sigma standards and the VP of Support works to improve the scores of support surveys. These assigned objectives are just the “what”, not the “how”. It’s upon each VP to devise the how, a strategy, to meet their given objectives (as well as the key performance indicators to measure the progress of their efforts). Once they devise their strategies, they hand down objectives (components of their strategy) to the directors under them. The directors in turn devise strategies and hand objectives down to managers, and on and on until finally we reach those with no direct reports, the majority of the employees.

In this day of the information worker, decentralization of control, the delegation of responsibility, it’s more up to each worker to devise how to accomplish their objectives. It’s far from anarchy. We’re still expected to stick within myriad government and corporate guidelines and are usually expected to prove that our “how” has been tried many times before with great success (meaning, trying new things doesn’t happen very often because no one is willing to be the first). But we still have much wriggle room for creativity than if things were severely top-down, unambiguous, micro-managed directives.

At one corporation I’ve worked with, one with a highly competitive culture, there are about 3,000 managers out of a total of about 10,000 employees. That’s not as bad as it sounds since most of those managers are player/managers, such as a sergeant who shoots a gun as well as directs the actions of a squad. But that’s 3,000 managers struggling quarterly with devising strategies to meet objectives that are usually tougher than the previous quarter. That’s 3,000 different personalities, skillsets, points of view, points of pain, environments, social networks, etc. These assigned objectives aren’t just tougher because it involves simply a higher target for the same value, such as Sales. It could be tougher because it represents strategic shifts from above that require the manager to change as well.

So there are the 3,000 managers banging their heads against the wall figuring out to meet these challenging assigned objectives which are never as cut and dried as one would hope. After much booze and crying, they come up with a few ideas. Each of these ideas are a theory, a strategy. They consist of chains of cause and effect. For example, to achieve higher customer satisfaction ratings, I will improve the knowledge of the support personnel by placing them into a smaller room where they can overhear other conversations, increasing their knowledge of problems that pop up for our products and reducing the steps needed to find someone who may have already encountered that problem. For now, just note the negative side-effects this strategy could have.

Remember, this strategy is just a theory. Many funny things can happen during that trickling down of objectives from superior to subordinate. For example, as the trickling down gets wider and wider:

  • The spirit of the original strategy can get lost in translation. This is no different than how a story evolves as it’s told from person to person.
  • They can begin to conflict with or even undermine each other, hopefully always inadvertently. In a corporation with thousands of employees, the efforts are bound to conflict or have contention with others.
  • The strategies at whatever level could be wrong, whether too risky or too naïve. A strategy is just a theory.
  • The chosen KPIs could be the wrong things to be watching.

But it gets worse. During execution of the strategies, many things can happen as well that thwarts the corporation’s efforts:

  • If the “theories” of the strategies at any level are wrong, once a bad strategy is selected, subsequent strategies by subordinates will address things incorrectly.
  • Things fly out of left field throwing the game plan out of control. “Black Swan” (if it hasn’t yet happened, it couldn’t possibly happen) events are not as rare as we seem to think (see Note #3). As the effects cascade through the enterprise, execution degrades into a free for all, with employees retreating back to their comfort zone of old habits that don’t work anymore.
  • Employees could game the KPIs. Meaning, they are able to meet or even rocket past their goals in a way that is easy for them, but probably has some side-effect to someone else. It’s amazing how clever people can be. So it looks like they are doing well, but in reality are not.
  • Employees may leave or even give up on reaching their goals as a sports team would be discouraged once they know they are mathematically out of the playoffs.

The points I list above (there are many more) make me wonder how corporations in the end do succeed. For one thing, they often don’t and die a quiet death. Those that do survive do because people are intelligent  and somehow figure out how to make things work, even if it was very painful. 

The number of moving parts within the corporation, for which they have at least some control, are so many they are indeed complex systems. Additionally, there are countless factors outside the control of the corporation, for which they have little or no control, which exponentially adds to the complexity. How things do actually work, or at least appear to actually work, is beyond the scope of this blog. I’m attempting to make the case for the need to take the process I describe above, Performance Management, to the next level.

Performance Management is a framework for establishing at least some level of order to that process. The most widely recognized tool is currently the Dashboard, a set of relatively simple charts and graphs, assessable through collaborative software such as SharePoint, where information workers can monitor the state of affairs. The primary object on a Dashboard is the Scorecard, a list of key performance indicators. A Dashboard is tailored to each information worker reflecting their KPIs and relevant chart.

F1 – Example of a Dashboard.

Another of these parts of a typical dashboard is a yet under-developed part called a “Strategy Map”.  A Strategy Map is a graphic of a network of initiatives pointing to what the initiative is intended to affect. For example, happy employees, leads to higher product quality, which leads to satisfied customers, which leads to more purchases, which leads to higher profit. It’s currently implemented as an almost static visual created in a tool such as Visio. Nodes on the Strategy Map may do things like match the color of the status of the KPIs, but other than that, it is just a picture. Like Dashboards, the Strategy Map is tailored to the role of each information worker.

F2 – Example of a Strategy Map. This is for a dental practice.

However, this strategy map is really the brain of the corporation whereas the Dashboard is simply the nerves indicating the state of being. It could be said that Map Rock is about bringing the Strategy Map to life. A brain is a much tougher thing to implement than a nervous system. This current decoupling of the Dashboard from the Strategy Map is dangerous since we will supposedly take actions based on what we see from the Dashboard. Just about every action has side-effects. Without a flexible connection to cause and effect, which as of now exists pretty much solely in our heads, at best, we jump in with the faith that those side-effects will be innocuous or we will cross that bridge when we get to it.

This “Business Problem Scenario” may be set in a corporate environment, but any endeavor is executed in a similar manner. The ultimate goal may be something other than financial profit though. This could be a non-profit devising strategies for implementing its cause or a government attempting to understand the effects of laws that it passes (yes, I do have a sense of humor – and understand I may have just flushed all my credibility down the toilet).

Coming up:

  • Part 3 – We delve into a high-level description of the Map Rock software application, where it fits in the current BI framework, and how it differentiates from existing and emerging technologies. This is really the meat of the series.
  • Part 4 – We explore strategy, complexity, competition, and the limitations of logic.
  • Part 5 – We close the Problem Statement with a discussion on imagination, which is how we overcome the limitations of logic, and how it is incorporated into Map Rock.
  • Map Rock Proof of Concept – This blog, following the Problem Statement series will describe how to assess the need for Map Rock, readiness, a demo, and what a proof-of-concept could look like.

Notes:

  1. The term “art” has been used in a disparaging context. People snidely refer to an endeavor that is not just repeating a successful process as, “It is more art than science …”. To me, art is a combination of a imagination and a high degree of skill to manifest what is imagined. And imagination isn’t something we outgrow out of childhood. It’s really what separates humans from the birds and reptiles. Art is not just fine art – which does require a great amount of skill and imagination. All things that didn’t exist at some time required imaginative and high-skilled people to navigate an unclear path.
  2. Rise of AI and Robots. This is probably the most relevant force to Map Rock. Many jobs seemingly outsourced to other countries or lost through mergers are never coming back. Why would anyone hire an army of people to dig a ditch when a backhoe can do the job faster, better, and more cheaply (by today’s wage standards). A friend of mine who worked in an auto assembly plant in Grand Rapids during the 1960s, but left to do other things, recently visited an auto assembly plant. He was shocked by the seemingly endless line of people replaced by a line of robots and relatively few operators. People have been predicting this for decades and we aren’t yet ruled by robots. But the trend is certainly that every day, AI and robotics will impinge upon the work available to humans today.
  3. I probably don’t need to mention that “Black Swans” are a notion popularized by the book, “the Black Swan”. They are events that no one would have even known to attempt to predict and with a large impact on things. However, in a world as complex as ours, such events happen much more frequently than we’d like to think at smaller, personal scales. I believe this underestimation of them is because we generally only think of the spectacular ones like 9/11 and the effects of Hurricane Katrina. However, a stroke or heart attack on our way to work on what is otherwise a day like any other is just as impactful to us individually and those close to us. I recall my father in the hospital for his bone marrow transplant just before the first Gulf War turning away from the TV saying he had his own battle to deal with.

About Eugene

Business Intelligence and Predictive Analytics on the Microsoft BI Stack.
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