Tag: demand driven
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Revealing Patterns of Change
This is Fun, But Not When You Are Under the Gun!!!
Gartner has launched a new focus area called “Pattern Based Strategy”, based on the need of businesses to capitalize on large amounts of data and the new rules for business process adaptation.
Here is a great verbatim quote from the Gartner web page.
The depth of the recent recession blindsided most businesses. As the economy starts to recover, many business leaders are thinking, “If I had seen this coming sooner, I could have acted faster, decreased my risk and enhanced my opportunities for growth.” There is a way to see things coming. It’s a framework for proactively seeking and acting on the early and often-termed “weak” signals forming patterns in the marketplace. It’s also about the ability to model the impact of patterns on your organization and identify the disciplines and technologies that help you consistently adapt. It’s called Pattern-Based Strategy.
The key to Pattern Based Strategy is automatically revealing intelligence that is hidden in the data/information. Companies today are running more lean than ever before. Employees across all organizations are inundated with work and overloaded with data. . There is a great need for technology that will make our jobs easier and make us more productive. At Gartner, the idea that emerged, led by Yvonne Genovese, is called Pattern-based Strategy (PBS).
We are victims of too much information, missed opportunities and ‘@#$% I wish I could have seen that!‘ moments. Connecting this to a rather timely/charged topic – Think about a recent attempted terrorist attack by the Nigerian traveler who bought a one-way ticket, paid in cash, checked no bags, boarded an international plane. There were a very large number of ‘red flags’ in the sequence of events, and there was a large volume of data hiding all this intelligence. A Hope Strategy is to hire tons of people and make them search the data for red flags, more importantly sequences of red flags. This may work sometimes. But it is a poor and expensive strategy, and rarely does it produce the desired results on time! (making it quite useless, actually!)
As companies start to incorporate intelligence from data into their operations, one of the primary issues is the ability to have the intelligence automatically come to you. ‘Digging for insight’ is a poor, time consuming, expensive strategy. We need the technology to work for us. Second, it is also important to start focusing the insight with a particular business function/strategy in mind. Sales, Marketing, Operations, etc.
Connecting this back to what we do, Emcien provides analytics that automatically reveal customer buying patterns in sales data. The analytics reveals the popular choice combinations, key differences by region, key trends and new emerging segments. This is an example of technology working for you, bringing insights back so that you can act on it.
Quoting a Regional Practice Manager and the Senior Architect for Siebel -
Emcien offers rigorous and repeatable detection of buying patterns, enabling your customers to act on them, while supporting your product objectives (margin, inventory, velocity, …)
Quoting a former Oracle Practice Manager and Senior Siebel Architect -
Emcien offers rigorous and repeatable detection of buying patterns, enabling your customers to act on them, while supporting your product objectives (margin, inventory, velocity, …). Emcien’s offerings readily integrate with Siebel, enabling immediate improvements to revenues. Few projects offer such potential for improving the customer experience and increasing revenues, with so relatively little development or integration efforts.
Automatically revealing patterns is required today as we all drown in data, and do not have time to hope that someone may find the intelligence that the organization needs to act on. Thanks to Gartner for launching this focus area!
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Is your sales history self-encrypting?
Emcien’s mission is to find the actionable intelligence that is hidden in the sales history of configurable products. We call this SKU intelligence. Many companies, however, save their sales history in a way that keeps any patterns hidden forever. I call this self-encryption. Many of these worst practices began as a way of saving space at a time when storage space was expensive.
A configurable product is one where the customer has to make choices to customize the product to his own particular needs or preferences. The valuable patterns are in the way these choices are made. The sales history should be at the right level of abstraction: in terms of the choices that the customer made. Here are four ways you may be encrypting your data.
- SKU Numbers. SKU numbers identify unique product configurations. They are a great shorthand for keeping track of what has been built and what is sitting in inventory. But if the sales history is kept in terms of SKU numbers, and the definitions of those SKU numbers are stored in a different place, then you may not be able to decipher your own history. By “different place” I mean a different database, different computer system, or anywhere that is not part of the history itself.
- Part Numbers. Customer orders get translated into Bills-of-Material (BOM) so that the requested item can be built and delivered. But what happens to the order afterwards? Often it is saved in terms of the part numbers. The customer ordered “2GB of RAM”, which became part 123-XYZ-645A. This was the right part number for 2GB of RAM from a certain supplier during a certain period of time. Remembering 123-XYZ-645A may be important for some warranty issues, but it is the wrong level of abstraction for understanding the customer. Many customers ordered “2GB of RAM”, but they got many different part numbers (different suppliers at different times). Part numbers change constantly, and unless a complete trail of part number changes and equivalences is maintained, a history in terms of part numbers is irretrievably fragmented.
- Standard Options. Most manufacturers make different models of their products, and the different models come with different “standard options”. The sales history doesn’t mention these options because there would be so much repetition (let’s save space!). The problem is that the set of standard options changes over time, even though the model names stay the same. Which options were standard on Model ABC in September 2007? Who remembers?
- Product Packages and Option Bundles. This is similar to the standard option problem. Some set of options is bundled together and sold as the “Sports Package” for some period of time. So the sales history says “Sports Package”. What was in the Sports Package in September 2007? Who remembers?
The sales history should be self-contained, with a record of each unit sold, expressed in terms of the options bought by the customer. If some options were implied by others, but could have been different, then they should be spelled out. If the data is saved in the right way, then the patterns in how customers buy the product can be revealed.
The difference can be dramatic. The message below appears to be gibberish.
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But suppose we use the key that Dan Brown uses in “The Lost Symbol”: the magic square discovered by Benjamin Franklin.
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Then we see the hidden message: “Emcien can easily find the hidden treasure in your sales history”.
The value is that customers are speaking to you when they buy your products. This is the true Voice of the Customer (VOC). But due to the data encryption issue, companies are blind to this intelligence. Unleash this intelligence, and you can drive higher sales and margin by serving the customer with the right choices.
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Value of SKU Intelligence (What Are Customers Buying?)
One of the most frequent questions we are asked about Emcien’s methodology is “why hasn’t anyone done this before?” The answer seems obvious to us, but we should probably write it down once and for all so we can just point people to a definitive document.
Exploding SKU’s to attributes generates a LOT of data. It is only useful if this translates to actionable intelligence. As we all know, we don’t need more data. We need actionable items and recommendations to improve business. The simplest answer is that collecting all the attribute data for SKUs has not been done before, because the algorithms have not existed to farm intelligence from them. In this blog I am going to address –
- Why having the data with the SKU attributes is invaluable!
- What analytics capabilities are needed, if you have that data
- Value of having SKU Intelligence (To drive SKU velocity)
Consider a product that has attributes, and offers lots of variety, also called configurations. Almost all products come under that class today! Think car, computer, or cell phone. The product has features, and each feature has alternative options. For example, a car has an engine (V-6 or V-8), a body type (sedan or convertible), and a color (red, green, blue, black, or white). Any specific car has many choices for each of the features. Customers make choices on the features. Do you want the cloth seats or the leather seats? Do you want the DVD player? How about the iPod connector? Make a choice for about 30 features and you are done. This applies for shampoo, toothpaste, computers, light fixtures, consumer electronics, … all products that have attributes choices.
We consider a configurable product that has a large number of features, each of which many alternative choices/options. Notice that we have finessed the hierarchy problem by allowing only two levels: feature and option. A customer will typically call out only a few attributes during a purchase. They expect you to know how you can complete that spec to fill the order. That is the single biggest opportunity at every point of sale!
If we have data with attributes for every SKU, we can begin to talk about buying patterns! A buying pattern is groups of options that are bought together, like the red color with the convertible body style. Or the DVD player with the leather seats. Or the pattern might involve 3 options, 4 options, 5 options…. many options.
Auto detect most popular attributes in fastest sellers
This brings me to a very important point. If you have sales data with attributes, you need an analytics engine that will automatically detect and tell you what attributes are bought together and are highly popular. A reporting tool that makes you query every choice combination will NOT work! You will be very old by the time you get an answer to most popular choices, as there are millions of attribute combinations. Emcien offers an analytics engine with cluster analysis that will tell you what attribute groups are popular. This answers the questions – what are customers buying and what attributes are popular. This knowledge can also be used for planning the SKU definition and knowing what products need to be on the top landing pages of your web site/ store aisles. (SKU Definition is the list of attributes in the SKU.)
Once the SKU definition is in place, 75% of the cost structure and efficiency of your supply chain has been fixed ! Your supply chain operates under the assumption that the SKU definition is correct. What does this mean? This means that if you offer 2 SKUs with slightly different attributes, that could have been consolidated into one, the supply chain will suffer that cost and inefficiency. The SKU definition has to be optimized before you send it into the supply chain. This is a key driver to SKU inventory.
Customers buy products based on choices at the attribute level. If you cannot gather demand intelligence at the attribute level, you are out of touch with your customer. Customers DO NOT buy SKUs. They do not know the SKU numbers, and they do not care.
SKU Challenges Based on Supply Model
Your business falls into one of these categories based on your supply model (see table). Knowing what attributes customers are buying can dramatically improve your demand response. You will be able to improve -
- SKU definition -This means knowing how many SKUs you need and what needs to be in the SKU
- Demand Forecasting – You will be able to forecast demand at the attribute level, which is the level that customers are buying
- SKU Inventory - plan what to stock to have highest turns.
- Sales Productivity and Efficiency – If you know what attributes are selling together, you can implement an automated recommendation engine (EmcienMatch) and your sales rep can recommend a good choice to the customer during the ordering process. This is probably the single biggest value of knowing what attributes customers are buying. Your sales reps are a trusted advisor to your customers. If the sales person know that all customers of a certain type bough a particular configuration, he could recommend that choice to the customer. Win! Customer is happy because he done! Sales person is happy because he looks smart! You are happy because you increased your sales repeatability!
For our Nerdy Math readers, here is technical nugget that you will love:
SO – here is another reason why what Emcien does has not been done before. Statistics deals with numerically valued variables. A numerically valued random variable X has a domain that can be classified as a ratio scale, an interval scale, an ordinal scale, or a nominal scale. In a nominal scale, the numbers {0,1,2,3,…} are just labels and have no numerical significance. In an ordinal scale the numbers provide an ordering, so that 2>1 in some appropriate sense. An interval scale allows real numbers (like 3.27) and differences are significant, but ratios are not. The classic example is temperature. A difference of 10 degrees is bigger than a difference of 5 degrees, but 100 degrees is not twice as hot as 50 degrees. Finally, a ratio scale allows all of the usual numerical operations on real numbers. Most of statistics assumes a ratio scale, and almost all of it assumes at least an ordinal scale. This leads directly to the mean, variance, covariance, and correlation. It also leads to metric spaces with distance functions.
But we want to consider a random variable X that represents a choice between cloth seats and leather seats. You might argue that leather > cloth, because leather is more expensive. But what about color? Is there any sense in which green > red? We are really interested in nominal scales. We may assign 0, 1, and 2 to “none”, V-6, and V-8 respectively, but these are just labels. That has a profound effect on the statistics we can use. And beyond statistics, we will have to develop notions of proximity or closeness that do not depend on distance functions. So it hasn’t been done before because the mathematics you need is not the popular stuff that’s in the textbooks.
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Part I: Reporting, Business Intelligence, Data Mining, Analytics: Actionable Tasks!
Software vendors use so many big words and confuse customers. Our customers have often asked us to clarify – so here I go. The definitions in this article are based on research of these terms, and the collective opinion of many of our customers and prospects. Over numerous conversations with our customers and the discussions of the terminology, the clarifications always go back to the origin of the terms and then move on to change in usage. Hence this article folows that flow. I would love your feedback as it is important to help buyers understand this.
Business Reporting
Business Reporting, as the term suggests presents the data from the database in an easy to read format. This originated when business users were frustrated that all the data was locked up in databases. There was a lot of data, but no one could get access to it without calling on IT folks. Hence Business Reporting was born.
Business Intelligence
This is a fancy name for business reporting. Business intelligence (BI) is a broad category of technologies that allows for gathering, storing, accessing and analyzing data to help business users make better decisions. In a 1958 article, IBM researcher Hans Peter Luhn used the term business intelligence. He defined intelligence as: “the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal.”
In 1989 Howard Dresner (later a Gartner Group analyst) proposed Business Intelligence as an umbrella term to describe “concepts and methods to improve business decision-making by using fact-based support systems.” Then in the late 1990s the usage became widespread (Remember the Bubble!). Then. everything with any data reporting was called Business Intelligence. So today, Business Intelligence is a glorified term for “Business Reporting”.
Data mining
Simply put, Data mining is hitting the data with all mathematical methods available to a mathematician! The data source can be almost anything – news papers articles, financial reports, sales data, medical data, … . This means that the data can have structure or can be un-structured. And the mathematical methods that can be applied can include neural networks, genetic algorithms, statistics on steroid and anything else they can think of.
One may ask – why are they doing this? What are they mining? Well, the simple answer is that they are mining the data looking for patterns; any patterns that can reveal relationships. So the methods used are varied and the kinds of data that are mined can come from a myriad of sources.
The results of data mining are lots of data! In fact – the result of Business Reporting and BI has been data overload. Now that’s the bad news. In a world of information overload, the last thing that we need is more data. We have less time today than we have ever had before. Business users do not need more data. They need quick conclusions on what the data is saying, converted into actionable tasks. Simply put – “Please tell me what to do”.
… More on the discussion of analytics to action in the next blog.
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Demand Driven For Configurable Products
Lane Strategy
It amazes me how sophisticated companies are getting with their supply chains. The recession has forced even more sophistication. As a way to weather the storm, companies are segmenting their supply chains to manage demand volatility better. I was talking to Jack Becker, VP of Supply chain for an electrical goods company, who described this as “3 lanes on the highway”. We just call it the “Lane Strategy”.
The fastest lane is the stuff that customers buy a lot of, and we build often. The middle lane is slower stuff, tends to be more configurations. The slow lane is the one-offs and custom builds. The key thing to remember is that the segmentation is demand driven, based on what customers are buying, and what is moving through the supply chain.
The key success factor for the lane strategy is to have a method to convey the lanes to the sales reps and distributors. Sales is the “mouth of the beast”, and it drives volatility and cost through the supply chain.
“We have had numerous attempts at trying to create a segmented supply chain ”, Jack said. “However, the sales guys will sell whatever is easiest to sell, and what they know to sell. So we had to device a way to make it easy on them to sell what we wanted the customers to buy.” Success finally came when Jack implemented a sales tool that would recommend configurations to the sales reps, and color code based on availability and the Lane Strategy.
“We offer a configurable product. Our biggest opportunity is that customers do not fully specify what they want. They just specify a few features they want, and leave the rest to the sales rep. They want the sales rep to recommend a good choice. Like we see on Amazon e-store…. But we are not selling simple stuff like books. Everyone on our team talked and agreed about an “Amazon like strategy”, and we knew that we needed sophisticated tools to accomplish that for our products, which are highly configurable. However – if our sales reps could recommend a few configurations at the point of sale, it is a win-win”.
“Supply chain folks typically think about the supply side of the equation. The key to success for a demand driven supply chain is managing the demand at the point of sale. Recognizing this opportunity and leveraging it has been the biggest key to our success!”
Emcien offers a product mix optimization solution that is a sustainable solution and process for the lane strategy.
More details on the execution of this strategy in the next blog….
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Self Service for All Configurable Products!
Configurable products are complex. There are so many ways the product can be configured! As the choices grow, it makes it more difficult on the sales reps and channels to make sure that they are selling the right product to the customer.
I was talking to a Steve Wright, VP of Sales at a company that sells a myriad of electronic and electrical products. He told me about the pain of training his reps on the product! “My guys just want to sell! I have them locked up for weeks on product training.” The company measured sales productivity and Steve was feeling the pain. “I don’t expect sales reps to memorize all the names and contact info for the customers they are calling on. Why do I expect then to memorize the products?”
Today sales tools (CRM) include contact management and pipeline management. However, products are changing faster than customer contact information. Who is helping sales reps keep up with that?
The challenges in the field are:
- Sales reps will only sell a few familiar products
- Customers often end up buying the wrong product variant
Steve has over 900 sales reps in the field. His challenges are sales productivity due to high turnover, and training (and re-training!). The bigger challenge is customer service and product returns because they were sold the wrong stuff. The product returns/ customer remorse is 75% higher for configurable products. The dissatisfaction of “being sold the wrong product” tends to make customers move to a competitor.
We all know of an industry that was completely changed when their products became very easy to sell. The products are highly configurable. So configurable that we needed a agents to help us buy their product. Today customers self-serve this product on the web, and we love it! The industry is airline travel. Airline tickets are highly configurable with a myriad of choices for airline, price, time, fare, stay-over options, alternate airports, ……. the list is endless. Self-service has also made it very easy for customers to educate themselves on the product at very low cost. An educated customer is better buyer and is more comfortable with the product they buy. The cost to sell the product has dropped very dramatically. When is the last time you called a travel agent?
The airlines that quickly embraced this revolution had a competitive advantage for over a decade. American Airlines led the pack with the Sabre reservation system.
The technology has arrived to make self-service possible for all configurable products. Companies who embrace it quickly will enjoy a competitive advantage in their industry. This is a truly demand driven model, driving much higher customer satisfaction.
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Unlock working capital by reducing inventory
More than half of companies recently surveyed by Aberdeen Group reduce inventory as their top response to tough times. The study, “Inventory Management: Three Key Strategies to Freeing Working Capital,” points out that using the right technology to manage inventory levels helps provide firms with a competitive advantage during the downturn and positions them well for better times ahead.
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How I want to buy a car
Every five or so years, I shop for a new car. I hate car shopping. The haggling, the long trips to dealerships way outside of town, the hours and hours of waiting, punctuated by furtive whispers to my husband, “Don’t give in! Stick to our budget! But don’t tell them our budget!” and similar. But that’s toward the end of the process. There’s a lot of work leading up to it.
First I hit the Consumer Reports site to research cars. A subscription is just $5.95 a month, but it auto-renews so you have to remember to unsubscribe or it quietly chips away at your wallet forever.
I find the five safest vehicles according to my car type and year. When I say new car, I just mean it’s new to me. I like to benefit from someone else’s new-car depreciation, which is something like 25% the minute you drive off the lot.
Anyway, I get on several different car sites like CarsDirect.com and AutoTrader.com to look for my next set of wheels. First I have to pick make and model, then enter my ZIP Code, then there’s a long list of cars. If I want to, I can see the list from lowest price to highest. The trouble is, I want to compare five different models and several different years. I’ve got to select the same filters over and over for all five and then compare the info. continue reading »
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Arm your salespeople to make the sale
I was talking to an executive at Oracle, and he told me that CRM is entering a new phase. Salespeople are the revenue generators of a company. Current CRM tools have served the purpose of helping salespeople organize their customers’ contacts and manage the sales process and pipeline, but this isn’t enough.
Your salespeople are representing and selling your product. Customers who want to buy your product typically list a few things they want and look to the salesperson to guide them. The salesperson is their advisor on your product offering. The salesperson is expected to know the product and suggest good choices for the customer. Is your salesperson equipped to do that?
There was a time when life was simpler and products were simpler. The customer said, “I want a 17″ TV.” The salesperson could look at what he had stocked and reply, “I have a 19″ I can give you for the same price.” Wow! Done!
Today, even the best salespeople don’t stay at one job for long. They move, selling what sells. Training sales newbies on a product is a big challenge for companies, and the cost of the salesperson not knowing the product he’s selling is VERY HIGH. As many as four out of five quotes are lost because customers weren’t guided to a good product selection. You can fill this gap by arming your salespeople with tools and product knowledge that will help them advise customers effectively on your product. Your company needs salespeople to have that capability so you can make money on the stuff they sell!
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Variation is valuable
Advances in interconnection technologies are driving an increasingly demand-driven market. Customers are learning to expect to get what they want, when they want it, how they want it. And they tell you in each and every interaction they have with your company, or not. In a demand-driven world, increasing product variation and complexity in your business model is inevitable. Left untended, your business can become a tangled web of counterproductive business strategies with a dense portfolio of product families comprising thousands, even millions, of variants.
However, make no mistake, variation is valuable. To deny complexity or view the long tail of product variation as a management failure is to deny diversity of the world in which we make our living. Eliminate complexity in your product offer and you will find yourself competing with boatloads of product from China, India or any of a number of low-wage production markets.
The “keep it simple” principle is the root of good management. However, as Oliver Wendell Holmes, Jr. has observed, “I would not give a fig for the simplicity this side of complexity, but I would give my life for the simplicity on the other side of complexity,” it matters which form of simplicity you choose. The wrong simple answer is to try to focus on the 20% of product variants that make up 80% of your revenue, the head of the ubiquitous Pareto distribution, and find ways to minimize or eliminate the so-called unprofitable remaining 80% of product variants that lurk in the tail. Hello commodity, goodbye margins. The right simple answer is to deliver Intelligent Variation based on the voice of the customer shouting through the many interactions they have with you each and every day.
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