*Illumiti is a member of United VARs, which is an SAP platinum partner.

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SMARTER,FASTER, ANDLEANERKeys to a successful ERP implementation

Introduction

I often meet with executives from our clients and prospects to discuss implementing a new SAP system or upgrading an existing one. In many cases, they’ve already decided to move forward with the enterprise resource planning (ERP) project and now it’s a question of when and how.

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When I ask the executives to share their benefits case for new ERP initiatives, the answer is usually some version of:• Our system is old (and its extension: Our system is heavily customized by two guys

who have been with the company for many years, and if they leave, we’re in trouble).

• We don’t have good visibility. It takes us too long to generate any reports, we run our business on spreadsheets, and we can’t see which client orders are profitable.

From time to time I get a more tangible reason that highlights a specific deficiency the company is trying to overcome so it can better serve its market (meeting service levels, stock availability, cycle times, and so on). But when I hear one of the above two reasons, I politely try to pick the rationale apart. The conversation usually goes something like this:

Me: Do you have a benefits case for this (new SAP) initiative?

Client: Yes. We know we have to do it, and we’re doing it.

Me: Great. Please can you share a few key business drivers of your benefits case?

Client: As you know, our business is very projects and services oriented. Our current system is old, and we have a lot of custom development that we really can’t maintain.

Me: Yes, this is a fairly common and significant risk. Would you mind giving me a little more detail: besides the custom elements you would like to eliminate and standards you want to

adopt, are there any specific areas of the business you intend to improve?

Client: Yes. We have very poor visibility today. It takes our accounting department over 15 days and roughly 30 cobbled-together spreadsheets just to get the month closed.

Me: That does seem onerous. How else does poor visibility show up at your company? In other words, what other issues does that cause?

Client: We’re often flying blind about the effectiveness of our projects. We can’t see that things are going wrong or that profitability is declining until weeks after the fact.

Me: If you had more real-time visibility, what elements do you wish you had access to, and what impact would they have?

Client: If there was a way to see real-time and projected profitability as we deployed resources on projects, I presume my project managers would get an early warning and potentially make different (better) decisions than the ones they’re making under the current circumstances.

Me: If you had those indicators readily available, and they led to better decisions, what impact could that have on the profitability of projects and the company as a whole?

Client: Not sure. Maybe 2 to 3 percent improvement per project?

Me: Since your revenue is roughly $1 billion a year, that would result in as much as $20 to $30 million in increased contribution!

Client: Wow – I didn’t look at it that way but you’re right – we would have a fairly substantial impact to our bottom line if we do this project right!

Even though I have oversimplified the impact to the bottom line, the conversation went from “old system and poor visibility” to a $20- to $30-million increased contribution per year! How can that be realized? By enabling better decisions (fewer mistakes) – in other words, by making the client Smarter!

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Why Smarter, Faster and Leaner?

Smarter, Faster and Leaner represent the key capabilities usually desired by most stakeholders. An ERP and a focused process by a good implementation partner can help them get there.

SMARTER captures the company’s need to enable better decision-making

throughout its value chain – not just better decisions by managers and executives but better

decisions by everyone, from the delivery truck driver and the forklift operator to the foreman, sales

executive and CEO.

FASTER represents the organization’s agility,

speed and overall responsiveness. Responding swiftly to all

stakeholders helps differentiate the company. Faster enables competitive

edge, as well as adaptability to changing business conditions.

LEANER is the company’s ability to scale and

do more with the same or less investment in fixed costs and

infrastructure.

Smarter Faster Leaner

We put Smarter, Faster and Leaner in that order because it represents the sequence of dependency.

Companies need to start by being Smarter. This improvement in effective decision making will help them to reduce delays, move more nimbly and improve service levels across the Organization (ie it’s a pre-requisite to becoming Faster). By being more agile, a company will expose waste and unnecessary expense that it can eliminate (Leaner).

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How can an SAP initiative make an organization Smarter, Faster and Leaner?

Over the last thirty years, ERP software has become very broad and deep in terms of functionality and capability. However, no matter what bells and whistles an ERP has, fundamentally it adds value by doing two things: 1. improving automation of manual processes and 2. creating transparency vertically and horizontally within an organization. Although both sound generic and high-level, all other ERP capabilities fit into one (or both) of them.

2Run a red traffic

light and cross safely

1Eat junk food

and gain weight

3Pursue a

new prospect and win

4Go on green

and get hit by someone else going on red

OU

TCO

MES

DECISIONS

GO

OD

GOOD

BAD

BAD

Smarter – Making better decisions (and fewer mistakes)If I asked how you knew if you made a good or bad decision, you’d probably use the quality of the outcome as a gauge. Decisions leading to a desirable or an undesirable outcome are usually viewed as good and bad, respectively.

The problem with this line of reasoning? There are many cases where making a bad decision yields a positive outcome, and vice versa.

Think of a driver who runs a red light in heavy traffic and crosses the intersection unharmed. Was it a good decision? No, it was not. But the outcome was positive. Conversely, if the driver decided to stop abruptly in order to avoid running the red light (good decision) but was rear ended in the process (bad outcome), does the think his decision was good or bad?

Because we seek a positive outcome as opposed to simply making a good decision, we need to analyze the elements that influence the outcome.

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First, a decision doesn’t directly lead to an outcome; it leads to action. Clearly a good decision and good execution have a material impact on outcome. But there’s a third element: uncertainty, which can result from lack of information or just luck.

Uncertainty creates the statistical probability that good decisions and skilled actions can result in negative outcomes, and vice versa. Please note that high quality of the decisions and high skill of actions increase the probability that the outcome will be favourable. But as long as the chance of a negative outcome isn’t zero, even a low probability sometimes yields a negative result, despite our best efforts.

So where can ERP make a difference in the quality of outcomes? It can:

1. Improve decision-making (Smarter).

2. Automate certain actions to ensure consistency in execution and eliminate errors.

3. Reduce uncertainty by providing end-to-end transparency.

When asked, most business stakeholders would say that having better data, better information and better knowledge help individuals to make better decisions and take better actions. But what does that mean, and what’s the difference between data, information and knowledge? To answer those questions, let’s look at the taxonomy of data.

Uncertainty creates the statistical probability

that good decisions and skilled actions can

result in negative outcomes, and vice versa.

Skill of Action

Uncertainty

Quality of Decision

OUTCOME

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For data to be usable for further processing

or analysis, it needs to be structured.

In 1992, I completed my Master of Science degree in engineering with a concentration in artificial intelligence. At that time, creating a practical application for AI was difficult because the discipline and its technology were in their infancy. One of the things we were trying to do is develop a clear and consistent set of definitions. To that end, my professor had me develop a five-level taxonomy as part of my master’s thesis. I’m sure there are other versions, but this is how I have always looked at data and its downstream evolution.

Data is a representation of facts, symbols, values and attributes. It is fundamental and represents the elements of our reality (whether we are conscious of it or not). Unstructured data is data that is not stored in a table or database and is not accessible or available for processing. For instance, I could

measure the temperature outside and learn that it’s 72 degrees F. This is data. But if it’s just captured on my thermometer and not entered into a database, there’s very little I can do with it. It’s just a fact. For data to be usable for further processing or analysis, it needs to be structured.

Taxonomy of Data

Level 1: Unstructured Data

Unstructured Data

Structured Data

Information

Knowledge

Wisdom

1

2

3

4

5

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Structured data is stored in a database (table) and easily accessible for processing. Again, data is just facts. Better data means better (or more accurate) facts. Usually when we speak about data, we mean structured data.

To move from Level 1 to Level 2, unstructured data needs to be captured. You can do this via user entry into an ERP—for example, when an inside sales representative takes a sales order over the phone, she is dealing with unstructured data. When she enters the parameters of an order into the ERP, it is now structured.

There’s also automated collection: voice recognition entering the same order automatically, a programmable logic controller (PLC) gathering data from shop-floor machines, a transducer capturing ambient temperature and storing it, Internet of Things (IoT)devices collecting outside data.

Because data represents raw facts, we want it to be as good as possible: accurate, timely and stored in a system so we can analyze it to support decisions. But facts alone aren’t enough, so better data, although necessary, is not sufficient for better decision-making.

Simply put, information is the answer to a question, or query. We obtain information by using a reporting engine to process structured data. “What time did the customer place sales order number 12345?” is a query. “At 9 a.m. EDT today” is information.

Good information—the ability to see and get to the data, process it and extract the answer—is essential to better decision-making as well as the reduction of uncertainty. There are two common challenges to getting information:

1. The data wasn’t easily accessible; usually a function of having multiple systems that aren’t integrated or data that simple wasn’t captured (structured). We tend to hear this problem from clients as “We have poor visibility.”

2. Reporting structures aren’t defined effectively, typically because needs change over time. Traditionally, key users have had to define those structures well in advance, so in real time, the resulting reports often don’t serve their needs.

Let’s say we have a predefined report that gives users the time a customer placed a sales order. Now assume that someone needs to know how much time elapsed between order entry and confirmation of delivery date. This apparently simple additional requirement is often not simple to implement.

Relying on traditional methods, that isn’t possible without modifying the report or creating a new one. You have to call IT, which logs, prioritizes and schedules a ticket—and if you’re

Level 2: Structured Data

Level 3: Information

Because data represents raw facts, we want it to

be as good as possible: accurate, timely and

stored in a system so we

can analyze it to support decisions.

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lucky, several weeks later you get the report. Then you need to know how many orders the customer placed for the same item in the past 90 days. Here we go again.

One of the biggest benefits of SAP’s S/4HANA (in-memory) architecture is the ability to define the query in real time and push that capability to an informed end user. This, in addition to ERP’s automating repetitive tasks

and creating end-to-end (vertical and horizontal) transparency is crucial to improving the quality and speed of information delivery so the organization can make better decisions. Having a system that doesn’t need predefined reports and can answer any question the business user has in real time is the vision we pursue as we strive to create the ultimate decision support environment.

Knowledge is familiarity and understanding of a specific subject or area. It is associated with the adverb “How”. In the ERP world, it covers how something works or how to do something. You can acquire knowledge through education (codification or configuration), or by learning from experience. Codification is a mature discipline, and coding/configuring best practices is a way of “teaching” the system how to behave under normal conditions. We can even code exceptions, setting up parameters for thresholds where the process changes accordingly.

Learning happens when feedback is received (and promptly after a decision and its subsequent action have taken place.

In traditional ERP usage situations, when we didn’t like a given outcome, we would recognize the issue (feedback) and code a new rule or exception into the ERP (learning). Although this doesn’t look like artificial intelligence (it is not AI) it is still a form of “learning”. Swift feedback is crucial for organizational learning. That includes the people getting better at their jobs, making

Level 4: Knowledge

We believe that one of the biggest benefits

of SAP’s S/4HANA (in-memory) architecture

is the ability to define the query in real

time and push that capability to an

informed end user.

Learning

Action

Feedback Decision

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The dictionary definition of wisdom is “the quality of having experience, knowledge, and good judgment; the quality of being wise. Synonyms: Sagacity, sageness, intelligence, understanding, insight, perception, perceptiveness…”

Building on Level 4, knowledge, my definition is that wisdom represents the ability to:

1. Learn experientially, taking feedback from actual outcomes and self-adjusting the rules and parameters of decision-making and execution in order to improve.

2. Diagnose past events. This mean explaining, proactively or on demand, why something behaved the way it did.

3. Predict possible future events.

This is the pinnacle of data utility. If knowledge focuses on “how,” wisdom focuses on “why.” Understanding why something behaves the way it does or why something will happen in the future are foundational to wisdom.

Level 5: Wisdom

Understanding why something behaves the

way it does or why something will happen in the

future are foundational to wisdom.

changes to configuration or coding exception as well as machine learning, where the system is self aware and makes changes to the “rule” without the intervention of a human programmer or operator.

To summarize, knowledge in an ERP is configuration and customization of processes (knowledge about the system), coupled with the information from effective reporting (knowledge about the business situation). We leverage this information to make better decisions.

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To make meaningful use of data to improve decisions, we must:

1. Capture as much data as possible in Level 2 (structured). Storage has become so affordable and available that the limitations of a decade ago no longer apply. Since we don’t know what questions we may have in the future, it is better to err on the side of abundance. If we can capture the data, we should.

2. Make sure the data is correct—that it accurately represents the most current reality.

3. Have an efficient reporting engine that provides timely answers to relevant questions.

4. Have effective and well-understood process flows configured to enable automation where possible and provide feedback when things go outside acceptable tolerances. For this to happen, the system must encapsulate the foundational knowledge of the value stream.

Smarter: Making better decisions (and fewer mistakes)

Speed is important for two main reasons:

1. Speed in serving a stakeholder (internal or external customer) is always a priority and can often be a differentiator. Speed at any cost is not desirable, and I’m not advocating for quality tradeoffs to achieve it. But all things being equal, speed—specifically, being faster than the competition —is a good thing!

2. Quick feedback is critical to the learning cycle and fine-tuning our knowledge. The faster and more relevant the feedback is on key decisions, the better decisions will become. If a decision isn’t achieving the desired outcome, speed allows the company to change course so it can mitigate any damage or improve the odds of success.

Quick feedback is the internal capability that together with being Smarter, will let you serve stakeholders better.

A prerequisite of speed is automation (which is one of the two main benefits an ERP delivers). An ERP achieves automation because it captures best practice rules (knowledge about the system) for the key processes that can and should be automated. The embedded feedback loops inherent in a well-designed system also enable it to provide rapid feedback and exception alerts, which makes the business more agile when it comes to course corrections.

Faster: Quicker and More Agile

Once the organization is Smarter and Faster, it will inevitably become Leaner. There’s a virtuous cycle at work here because the more we automate, the Smarter, Faster and Leaner the system becomes, which means there’s less manual intervention.

Eliminating manual activity from your business is a big deal, but contrary to popular belief, it isn’t about saving money on labor. The main benefit of Leaner is a significant reduction (and elimination) of mistakes in planning and execution, which makes the organization even Smarter.

Leaner: Doing More With Less

Automation

Faster

Leaner Less Manual Intervention

Smarter

End to End Transparency

Less Mistakes

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Conclusion

Setting our sights on achieving better outcomes is the key to success when implementing a new ERP. We can improve these outcomes by making the company and its stakeholders Smarter, Faster and Leaner. Smarter companies will make better decisions, eliminate uncertainty and establish good knowledge-based best practices to ensure topnotch execution. This will deliver more positive outcomes.

Smarter will also enable the business to be Faster so it can adapt to new business conditions, improve customer service and change course when it isn’t getting the desired results. Ultimately, both Smarter and Faster will make the company Leaner, allowing it to scale, manage costs and further eliminate errors due to reduced manual intervention.

At Illumiti, our purpose as a company is to make customers Smarter, Faster and Leaner. We invested and continue to invest in identifying and codifying industry best practices in our core industries so that customers can capitalize on the inherent automation, decision support and error proofing their most important processes. Since every customer and situation has unique attributes,

it is also important to go through a thorough analysis of which capabilities truly differentiate the organization and need to be front and center to ensure excellence and which are error prone or could result in material organizational risk – for these we need to increase the robustness of the system so it can withstand the inevitable bumps and bruises without extensive negative outcomes.

As technology and innovation continues to mature we expect more and more systems to extend capabilities into the “wise” tier (Level 5), become more self-aware, self-learn from positive and negative feedback and generally improve outcomes for the organization and its stakeholders.

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Larry Perlov, President of Illumiti Corp, is a veteran of the high-tech and consulting sectors with over 24 years of international executive-level experience in SAP, ERP, and IT infrastructure solutions.

Larry has extensive experience leveraging people, processes and technology to drive business value for clients. Prior to Illumiti, Larry was a Senior Vice President at IMG responsible for the Global SAP Business One business unit.

Prior to that, he was Vice President of Intuit Corporation Distribution Services and Director of EMC Corporation Client Solutions of New England. As a Senior Director at PLAUT Consulting, Inc. he was responsible for international SAP

implementations, which spanned business development and project and integration management. An expert in core SAP modules as well as process design and integration, Larry is a results-driven leader with a proven track record in business development, operations, and program management. He is noted for his ability to create and motivate high performance teams to drive SAP solutions excellence.

About the author

The information contained herein is of a general nature and is not intended to address the circumstances of any particular entity. No one should act on this information without appropriate professional advice after a thorough examination of the particular situation.

Copyright ©2019 Illumiti. All Rights Reserved. The Illumiti name and logo are registered trademarks.

Illumiti is a leading systems integration and management consulting company with offices in Canada, the U.S. and Switzerland, serving customers globally. Its team enables customers to realize their vision by leveraging the world’s leading on-premise and cloud-based business applications. Illumiti helps its clients achieve optimized operations in the key areas at the core of their business, by implementing custom-fit solutions from SAP and other vendors faster, at a lower cost, and at a lower risk than other alternatives.

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