Archive for August 2018

BURGERS, BULLWHIPS, AND BEERS! Taking Inventory and Costs Out of Your Supply Chain with SAP IBP!

We’re always looking for a good reason to have a cook out! We invited some friends over for a backyard bar-b-que a few weeks ago to celebrate. A few of our friends have kids, so we needed to know how many burgers, buns, and beverages to get for the big cookout.

We planned for 18 burgers to generously feed everyone. We love Bubba’s Grass Fed burgers and they are sold in packages of 6 burgers; we bought 3 packages. Our favorite rolls are the Kaiser rolls – scrumptious, big, fluffy rolls, great for burgers. They are sold in packages of 8 – all burgers were sold in packages of 6, and rolls were sold in packages of 8, how odd! We had to buy 3 packs of rolls. It seemed like such a waste and some of the rolls would eventually get thrown away.

This phenomenon is not limited to burgers and rolls and happens in a variety of ways across the supply chain. After doing some research, this is known as the Bullwhip Effect.

The Bullwhip Effect is a distribution channel phenomenon in which forecasts yield supply chain inefficiencies. It refers to increasing swings in inventory in response to shifts in customer demand as one moves further up the supply chain. Typically, this is a bi-directional issue; demand signal distortion up the chain, or supply chain integration down the chain.

At MIT, all incoming students play the Beer Game. The Beer Game simulates the complexities, assumptions, and inefficiencies that occur in a typical supply chain. This game has been played since the ‘60’s, and it continues to frustrate the smartest of these students. MIT also hosts the game for Fortune 500 companies with similar results.

How is the Beer Game played? Sorry, not with real beer!

Each team in the Beer Game consists of people at four stations, representing a beer retailer, a wholesaler, a distributor and a brewery. The team starts off with some chips on the table, representing cases of beer. Each round, up to 50 rounds, the retailer draws a number indicating weekly customer demand; players at the other stations write their expected demand on slips. The team circulates the slips and moves chips through the supply chain, but the teammates cannot communicate directly.

The goal is to run the supply chain as efficiently as possible. Each team’s four stations are penalized for an accumulation of inventory (50 cents per case of beer, per week), and for unfilled backorders ($1 per case of beer, per week). The team with the lowest score over 50 weeks is the winner.

Why are some of the smartest students and most admired companies frustrated by this game? They continue to use planning and forecasting principles put in place in the ‘50’s and ‘60’s.

SAP IBP helps to reimagine the forecasting, inventory, and supply chain processes to reflect today’s reality. Today’s reality reflects global supply chain networks utilizing outsourced partners i.e. contract manufacturers (CMO’s/3PL/s). This places tremendous burden and dependency that everything will run smoothly.

Let’s face facts, inventory levels will never be a perfect match of supply and demand. The goal is to minimize the stock outs and maximize customer satisfaction.

How can SAP IBP achieve these ambitious goals?

IBP leverages some key concepts in the DDMPR – Demand Driven MRP initiative that is the driving force behind a new approach to supply chain planning. You can read more about this approach and buy the book here.

Some of the benefits from using SAP IBP are:
• Improved Customer Service
• Reduced Lead Times
• Near Right Sizing Inventory
• Lower Supply Chain Costs

Two key concepts IBP uses from the DDMRP methodology is Decoupling and Buffer Profiles and Levels. Traditional MRP is sequential and changes at either end of the chain creates additional disturbances and distortions in the supply chain; the classic bullwhip effect in action. For example, if there is a change to an existing order or inventory level, MRP wants to fix it and will create additional orders, causing additional inventory.

DDMPR, by contrast is an independent model and it decouples supply and demand to minimize or block the bullwhip effect. This allows inventory levels to smooth out and recalibrate back to a normal range of supporting your metrics of customer satisfaction and working capital.

The second concept that IBP leverages is Buffer Profiles and Levels. IBP recalibrates the necessary inventory levels throughout the supply chain to guide the appropriate inventory levels. The stop light model guides the planners on the course of action. The action taken presents the various buckets related to order frequency and size, primary coverage, and safety stock.

Where are you in your digital supply chain journey? Do you need help digitizing and automating what you do best? Or do you need thought leadership on how to map your path to a digital supply chain?

Contact Joseph Lamb, joseph@titanconsulting.net, or call him at 972-743-2872; or contact your Titan Consulting Director. You can also see additional information on Titan Software at Titan Consulting.

SOLD A DIVISION? HOW TO DIVEST YOUR SAP DATA! Our Expertise in SAP Landscape Transformation (LT)

You saw the announcement on Bloomberg! Wall Street is applauding the news as the stock ticks upwards! Everyone is excited, but now the head-scratching work begins – how do I break out my SAP system and separate the divested data?

Divestitures are commonplace. What is not so common and often complex is how to manage the data according to the terms of the divestiture. The TSA (The Severance Agreement) typically defines what stays and what goes. A primary driver around the right approach and effort is the sensitivity of the data – what data do you want the acquiring company to see.

Helping some of SAP’s largest customers with divestitures we provide knowledge, expertise, and assurance that your divestiture happens in your timeframe.

The various approaches to divesting your SAP include:
• Carve-Out
• Clone and Go
• Transfer
• Data Masking

A carve-out is the most common approach for a divestiture. When you leave on Friday the divested company and related data is there. On Monday when you return, it’s gone; there is no trace of the divested company except an audit trail.

One example of a carve-out project we successfully completed on time while guaranteeing the results. A high-tech company had to delete all traces of the divested business. The carve-out included configuration, master data, and transactional data.

SAP Landscape Transformation (LT) is the perfect tool for this type of project. In this situation the data was organized at the Company Code level – the most straightforward approach ensuring a successful outcome on a tight timeline.

Not all divestitures are this straightforward, requiring more planning and effort. If the divested business was organized either above or below the company code, expect additional complexity, effort, and duration. For example, the business is organized across Profit Centers, Business Areas, Plants, or by global Business Segments, these models are inherently more complex.

Another business case, a global chemical company sold off a division to a competitor. The TSA required that ALL related data must be removed from the existing system. The selling company did not want their competitor accessing any trade or operational secrets.

However, after reviewing their landscape, data schema, and business processes it was determined the data was commingled at lower levels. For example, sales orders, deliveries, and invoices contained line items from the divested and retained business units guaranteeing a 100% deletion of all the data was not realistic or reasonable, e.g., deleting line items causes the header data to go out of balance with historical values such as amount, pricing, freight cost, weight, and more.

The line item details were needed to support the header information for compliance, audit, tax, and financial reporting purposes. After the TSA was revised several times, they engaged us to help finalize the agreement.

We met with the stakeholders including CIOs, CFOs, and attorneys for both companies and advised them on the realistic options, timeline, effort, and assurances based on our system analysis and comparable results we provided for other clients.

Our solution combined the best of LT’s capabilities plus some creative expertise of our own to deliver the system. The solution included plant reallocations i.e. change of ownership of plant from one company to another, deletions, and data masking to ensure all data was removed and confidentiality was not compromised.

The other options; Clone and Go, Transfer, and Data Masking, are dependent upon the nature of the divestiture. We have advised and guided some of SAP’s largest customers on the options and the right Roadmap on divesting, harmonizing, reorganizing, and consolidating their SAP environments – and we guarantee your transformation results!

Our clients have used our experience and capabilities to drive transformation projects, assessments, SAP Landscape Optimization (SLO) and Landscape Transformation (LT) workshops and training sessions.

If you want clarity, confidence, and assurance on how you can successfully transform your SAP Landscape, contact, Warren Norris at 972.679.5183 or warren@titanconsulting.net to arrange a call to help you with your SAP Landscape Transformation.

BIG DATA FORCES BIG DECISIONS! How to Tame Your Data Management Beast!

Data is exponentially increasing every day! According to EMC, the amount of data is doubling every year. By the year 2020, there will be an estimated 44 ZB; a zettabyte is 1021 bytes.

Put another way, in the year 2013, a stack of tablets containing the world’s data would stretch two-thirds of the way from the earth to the moon, about 160,000 miles. By the year 2020, the tablets containing this data would stretch to the moon and back 6.6 times or approximately 1.6 million miles.

How do you take charge of your data management beast? Or will you treat it like the US government treats the deficit and kick the can down the road?

Designing and implementing an enterprise data management strategy, also referred to as Information Lifecycle Management (ILM), is a tricky problem. In many companies, this problem does not get the priority it deserves. Excess and ill-managed data cost you time and money. Think about this the next time you perform a client copy or worst; you can’t perform the client copy because it takes too long.

In the past, archiving was the answer. In some cases, archiving is still in your data management tool belt, but most likely, it is only one of many strategies and approaches to managing data.

One question many companies can’t answer – “What is the value of my data?”

Here are some quick facts:

  1. On average, only 15% of your data – all data – has value or is used
  2. 1/3 of your data is temporary data – such as log files
  3. Estimated cost of in-memory data is approximately 1 million dollars over three years

Here are three simple steps to help you assess and manage the value of your enterprise data:

  • Update Your Enterprise Application Inventory List
  • Forecast Your Data Growth
  • Synchronize Your Plans With Your Applications Roadmap – Especially HANA

Update Your Enterprise Application Inventory List

A portfolio of applications should already exist. Assess how each application fits into your Data Management strategy. This is usually quickly assessed based on owners, users, usage, and how digital business processes are impacting this application.

The outcome of this assessment becomes an input to your data management policies. You may be surprised by the overlap of applications and the hidden costs of redundant data that exists and becomes a quiet cost-driver – excess and redundant data does cost you time and money.

Forecast Your Data Growth

For your Enterprise Applications, forecast your data growth, consider how digital processes will impact these legacy processes. Adjust your forecasts for modern technologies such as IoT, Analytics, In-memory platforms, and the related impact on the stack.

In a recent article, we proposed guidelines on how to segment your data between Hot, Warm, and Cold data. See the recommendations from this article titled “WHAT TEMPERATURE IS YOUR DATA? Planning for your HANA Upgrade!

Synchronize Your Plans With Your Applications Roadmap – Especially HANA

How often do you hear the phrase,” I will buy more storage!” Do you buy a bigger house when your garage is full of old clothes and furniture? No, you clean it up, get rid of unwanted stuff that does not add value and takes up space.

Why would you continue to buy more storage when your data volume is larger? You still need to perform some housekeeping – archiving activities – and get rid of the unworn items. Performing the design and implementation of a more complex enterprise data scheme is more costly and takes more time to get results.

If HANA is part of your Roadmap and it should be, it is important to put a strategy and plan in place to rationalize your data. You pay a premium for in-memory storage and carrying excess data increases your investment and lowers your ROI – more data, higher cost, less value, lower ROI.

Check the facts from above; you use only 15% of your data. Implementing a Data Management Strategy consisting of data tiering and periodic housekeeping will help you run more efficiently and economically.

Ask your hosting or cloud partner how they manage this for you. The answer you hear is they will implement your strategy or adopt their standard practice – who knows your data better than you?

Big Data does create cost, performance, and management issues for you. At a minimum, implement an archiving strategy and execute it. If you do not have an archiving or Data Management Strategy in place or need an experienced team to review your strategy, contact Blake Snider, blake@titanconsulting.net, 469.835.5358; or your Titan Consulting Sales Director.