BHR Global Associates, Inc. is dedicated to helping companies bring their products to market successfully. We can help with finalization your design, to helping find the right source at the right price, help you maintain a solid on going supply chain and help you sell the product through our team of sales professionals. Our blog will supply information and details on successes, failures, and road blocks to avoid in bringing products to their full potential.

Wednesday, December 29, 2010

Dealing With Retail, Etc.

Thanks to Lora Cecere for her input on this post.

Over the past six years, I have studied the use of downstream data, and watched consumer products companies inch along, ever-so-slowly, with pilot projects. While I challenge my readers to take a leap of faith (reference prior blog post, and aggressively use downstream data (E.g. point of sale, warehouse withdrawal, loyalty and retail demographic data), I also want to equip them for the journey. It is not as easy as it sounds. There are pitfalls and landmines, and major obstacles to overcome.

Last week, I was in Chicago working with clients on the use of downstream data and the design of Business Intelligence (BI) strategies to become demand driven. Like many clients, these companies were in the middle of an Enterprise Resource Planning (ERP) upgrade cycle, and wanted to put downstream data into ERP to use the data to be more demand driven. I ruined their day, when I told them that I could not endorse their approach. Which led me to sharing the three things that I have learned about the usage of downstream data with these teams:

-It is not about Integration. This is too simplistic. It is about the synchronization of demand data. To synchronize and use the data, it must be cleaned, harmonized, and enriched based upon a carefully crafted data architecture and road map. Unfortunately, for many companies, they learn too late that ERP is not the de facto enterprise data model.

Data coming in from retailers represents their data model. To use the data (for anything other than sales reporting), the data must be converted to conform to the enterprise data model for product (hierarchies of selling units), customer ship-to locations, and corporate calendars and augmented with shipment and order data from Enterprise Resource Planning. Since most data in ERP is the manufacturing unit—not the selling unit—and represents ship from (what should be made at a manufacturing plant)—not ship to or the retail channel—the ERP data must also be converted to a standardized logical data model. Stuffing downstream data into ERP and ignoring this process is like stuffing a square peg into a round hole.

-Design with the End in Mind. In the organization, there are multiple use cases—sales reporting, category management, trade promotion management, replenishment, demand planning, improved transportation planning, cost to serve and client profitability modeling, inventory reduction and obsolescence reduction, item rationalization, shelf compliance sensing, new product launch success and demand orchestration processes (to translate the demand plan into buying strategies), Each of these use cases requires a different frequency of data –daily data/daily, daily data received weekly, weekly data received weekly, etc—and data enrichment schema. As a result, data must be held at the lowest level of granularity.

The problem on usage happens when companies start with simple use cases in the front office and as they mature, the requirements to use the data change and mature. To enable this process, companies should design a data model with the end in mind, and store the data at the lowest level of granularity to ensure flexibility in aggregation and reuse (note the Coca-Cola data model presented by Data Ventures on 12/17/2010 in figure 2). In doing this design, teams will quickly find that the data model that works is not ERP.

-Cultural issues Abound. Attack them upfront! While companies want to quickly point out the issues on the use of downstream data, the greatest issue lies in retooling the organization to “embrace new concepts, and think about the art of the possible.” To do this, five change management issues need to be addressed up front:

1) A shift in focus from “ship in” to “sell through” in the channel. The traditional approach encourages companies to push product into the channel in a very efficient push-based supply chain. As companies move from push to pull, they realize the need for push-pull decoupling points and the need to sense and use multiple demand points in the channel simultaneously through new forms of predictive analytics.

2) Realization that syndicated data is wrong. A barrier for the team is the traditional paradigm of “why do I need point of sale data, if I have syndicated data?” After many weeks, it becomes clear that the sources of syndicated data are inaccurate and that there is enormous value in seeing channel movement 3-4 weeks earlier than you can see it through syndicated data usage. A barrier is the high dependency of marketing and sales organizations on syndicated data, and the unfaltering belief that it is sufficient.

3) Redefine what good looks like. The traditional definition of the supply chain changes. Organizational incentives reward vertical silos. Sales incentives are to sell volume, marketing’s are to improve market share, and supply chain is rewarded to reduce costs. As companies use downstream data to build horizontal processes—a shift from north south to east west processes—the definition of supply chain excellence changes. Companies realize that supply chain extends over go-to-market activities of sales and marketing, and can be used to improve revenue management, channel sensing, and new product launch. However, companies can only get there if they give themselves the permission to change focus from inside-out processes to outside-in processes.

4) Right stuff. The organization needs to reward inspiration, perspiration and innovation. These initiatives are being driven at the director and manager levels not from the top down. These three characteristics are prevalent in companies that have leap-frogged the competition. In these organizations, there is a line of business leader with a clear vision, and the power to influence and persuade to get funding. There is also investment in back office analysts to look at the data differently—to let the data answer the questions that we do not know to ask—so that companies can reap maximum value.

5) New concepts. Companies are not used to thinking about demand latency and inventory velocity. Enterprise applications focus on data integration not the rate of change. It is a different focus and requires a different mindset.

It is hard work. It is cross-functional. It is a new way of thinking. At the core, it challenges traditional paradigms. However, if you can cross these boundaries, companies find that the use of downstream data pays for itself in less than six weeks every six weeks, and companies that were good at the use of downstream data and sensing channel demand aligned and transformed their supply chains 5X faster than competition. Procter and Gamble attributes their work with Terra Technology and the use of downstream data to a 2.5 billion dollar reduction in inventory. Jim Temme, previously of Anheuser Busch attributes the use of downstream data to a 20 million dollar improvement in trade promotion spending. Three companies have given recent testimonials at industry conferences on the use of downstream data to improve shelf sensing prevent voids and no-scan with a return in days. And, if this is not enough, consider the changes coming in 2011:

-Wal-Mart is upping the ante for many manufacturers on penalities on trucks that are not delivered on time and in-full up to 3% of the value of the truck.

-Kroger and Safeway data programs are launching increasing the ability for grocery manufacturers to get signficiant channel concentration of data to manage the demand signal from the outside-in. The increase in point of sale data in the channel is a great opportunity to improve the supply chain response.

-The need to tie digital and social programs to brick and mortar programs. Retailers are asking companies to shape demand in the store through social programs. Demand elasciticy for social couponing programs is 100X the response of store circulars necessitating a responsive supply chain. But, how can you be responsive if you cannot sense?

With that, have a great holiday season and a good new year. Maybe, just maybe, the serious use of downstream data will be on organizations’ New Year resolution for 2011. In the words of The Night before Christmas, “now dash away, dash away, dash away all.”

Sunday, December 19, 2010

To Patent or Not To Patent

Getting a Patent isn’t Always the First Step.
When starting out the first things to consider would be the marketability of the product, cost of the manufacture and the technical considerations. If you need help in those areas there’s more information on this site that may help you with those concerns.
Having said that, let’s look at what happens to a typical US patent application, and at what cost and time are involved. Some US applicants will not follow the same course as outlined here. While in Countries outside of the US may have a completely different process.
The First Step in the Patent process: Do a Search (Costs approximately $300-1500; Amount of Time Spent 1-3 Weeks)
The first step to take in the patent process would be the “novelty search”. The search will give you a better idea of what kinds of protections are available. Both the cost and time to conduct the search will vary depending on the invention. The cost of the search should be around 10% of the total cost of patenting the invention. If you know your market well and you believe your competitor may beat you to the patent office maybe it would be best to skip the search. But for the most part this is a very important step.
The Second Step in the Patent Process: Preparing and Filing the Application (Costs Approximately $3000-8000; Amount of Time Spent 1-3 Months)
The second step in the patent process would be preparing the patent application. The time and cost are going to vary and will depend on the invention and if your disclosure materials are up to par. depend on the complexity of the invention and on the quality of the disclosure materials that you’ve put together. When completing your application you should do so carefully to avoid mistakes. Make sure to read over your first draft and make corrections as necessary. Most instances you will go through a few applications before you have a perfected application. Expect to draw pictures of your invention. Adding informal drawings will speed up the application process.
The Third Step in the Patent Process: Plan on a Long Wait (Approximant Time 14-24 Months)
When filing for a patent in the US, plan on waiting 14-24 months for most inventions. Rarely an application will be reviewed within 4 months of filing. The more popular the technology is expecting a longer wait. This really isn’t all that bad, considering if the PTO takes longer than 14 months to send the examiner report, your patent can be extended a day for everyday in which there is a delay.
The Forth Step in the Patent Process: The Examination and Possible Appeal (Costs $400-$1000; Time Table 1-3 Months)
After your long wait a patent examiner will read your application and compare it to what he or she thinks would be the closest prior references. In the US, 95% of these initial examination efforts lead to objections to formal features of the application. This is when you and your attorney or agent will have to come up with a fix to the problem. You will than need to appeal the decision by proving that the examinee came to the wrong conclusion.
This appeal to the examiner will be handled much more quickly than your first application. This part of the process will normally take about 2 months.
The Fifth Step in the Patent Process: Approval (Costs $700-$2000, Time Table 1-3 Months)
At this point 70% of US applications will be allowed. The communication that you will receive from the examiner will either be an acceptance letter or a rejection letter. The good thing at this step is that most applications will be accepted at this time.
What Could Happen During the Fifth Step: Publication
In most cases the patent application will be published within 18 months. If the application was only filed in the US, there may be an exception and be kept secret until the actual patent is issued.
The Final Costs and Time
After the process is completed expect to have spent a total of $5000-$10,000 within a three year period. These are US. Prices, if this were done in another country it may cost much more.

Sunday, December 05, 2010

To Patent or Not To Patent

The answer is simple depending on what you plan to do with your idea.
If you want to bring it to the retail market then I would suggest you spend your money on product development and NOT on a patent. The protection you will get from a patent will do you no good if no one wants to buy the product and the time and money spent waiting for the patent to be approved will be better spent making prototypes and getting costs for the product.
If you are looking to LICENSE your prodcut and not go into business for yourself then you definitely need to get a patent to protect yourself once the product is ready to discuss with potential partners.
Typically you will receive between 3-5% of the wholesale price of the product as a licensor from the licensee.
Another alternativ eis to be a vendor to a licensee and make product for them and potentially make more money than a direct licensor only.
In either case insure that any contract between you and the licensee has a performance gusrantee and an out for you if the licensee is not hoolding up their end of the bargain.
In going ahead with your product do your research on if it exists and then layout a plan on how you want to go to market.
Be wise on how you spend your money because you can go broke otherwise.

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