Process Redesign – Do it right or go home.

Posted on October 20, 2011 by Gene Tanski

When approached without a clear understanding of the technological possibilities and a relevant examination of the organizational structure and policies (i.e pay) supporting it, Business Process Redesign is a complete waste of time.

In fact, I will go so far as to argue it is a destruction of shareholder value to invest time, human resources and actual cash in pursuit of improvements that will be minimized and/or never realized.

So what are the risks of the so-called “People, Process, Technology” approach?

You can only contribute your process requirements based on what you know, but you can’t know the possibilities inherent in technology platforms until you’ve explored them
You might design a process that only stays relevant for a year rather than 5 years and/or necessitates expensive upgrades, training and consulting fees with every step
You might end up paying people to perform the old process, not the new process
Your technology may require costly customizations or “work-arounds” to manipulate data outside of system support in order to support the new process

Say your current process involved 4 or 5 steps – it begins with a query to get historical data, extracting that data to a forecasting engine – something like excel or Demantra (no real difference), then running the model, then organizing the output into a useable format, running a series of reality meetings with Sales, Marketing & Operations and then finalizing the execution forecast.

Now, given that background and experience, in a typical process redesign, you would enter a room with big whiteboards or brown paper sheeting taped up and most likely a consultant (internal or external) standing at the front of the room saying – please – give me your requirements so we can design a process. What are you going to pull from in order to provide requirements? Your experience – what you know. Which means in effect you will be paving over cow paths – which might be charming in Verona but not the basis for delivering competitive differentiation for your company.

Perhaps even more frustrating is say that you are able to think out of the box and come up with a truly radical process that cuts out 4 of the 6 steps and if properly executed would increase accuracy by 10% and reduce cycle time by 75% and help improve order fill rates from 90 to 99%? And then you go out and look for a technical platform only to find there is no technology to support your process? Can you say frustrating loud enough?

So what is the right way?

Technology – Process – People

A comprehensive, holistic approach based on the principle that Technology should support Business Process, and Business Process should exploit the capabilities Technology can provide – Davenport & Short dubbed this recursive view of Technology & Process Redesign “the New Industrial Engineering” — Rather than lay out a step by step detailed process (proscriptive process design) you outline specific outcomes for the project (outcome based process design).

This would include:

Identifying what is wrong with the current process,
Creating a general vision as to where you think the current process could improve,
Setting specific measurable goals for improvement – including areas to focus investment and amount or degree of improvement desired.
Considering your pathway toward maturity – how much will it cost to improve down the line?

Within this framework, you can then invite technology providers in for conversations and focus on finding a partner with a technology that can provide measurable performance improvements as well as a platform that is flexible so that it can stay relevant for this process as well as future required changes as your business continues to grow and evolve.

Once you have a partner chosen based on technological prowess, flexibility, industry knowledge and compatibility, you can then engage in detailed process design in tight partnership with the technical platform you have chosen. You can then also do a review of compensation structures and organizational design to ensure these will be flexible in supporting new process and performance expectations.

[Quick word of warning: This does fly in the face of the normal RFP process where a company says, “Hey, we want to do something but we are not going to share the specific details or outcomes we are going to measure nor any of our criteria for success.” What ensues within the responders is a process of guesswork, misdirection, outrageous claims and leverage which, in many cases isn’t entirely dissimilar from a season of “Survivor.” And yet, after it all, many executives end up choosing based on faulty assumptions about long-term cost savings and NOT business outcomes.]

There has been specific research done on this by a few groups and the statistics are frightening:

70% of process redesign projects fail to deliver on the business case and the budget. Only 30% actually hit the minimum marks!!

The holistic approach, however, produced strikingly different results.

50% reduction in total project time,
35% reduction in total project cost,
70% improvement in technology uptake
60% improvement in attaining business case

This really seems like a no-brainer but yet, as noted at the start, people are still approaching corporate performance improvement like it’s 1985.

How can we evolve this conversation beyond old paradigms? What can be done to help drive efforts to improve corporate performance such that our companies not only survive but thrive?

More about our forecasting and planning software.

External Data – The Next Frontier

Posted on December 7, 2010 by Gene Tanski

Considering External Data in Demand Planning

When you make business decisions, you are almost always looking forward. You’re thinking about the future. This means you’re thinking about forecasting and planning. And what this really all means, is that you are thinking about demand.

When you make critical decisions around demand, you need information from disparate data sources about your market, your customers, the economy, the weather, your costs, your profit margins, what your competitors are doing, your ability to stimulate demand, your company’s capacity to meet the expected demand, among other things.

When thinking about all these factors, and when looking into the future to make these decisions and achieve the desired outcomes, it seems obvious that we have a problem. The data that has historically fed the forecast (past orders, past shipments, last month’s prices) is going to be less than adequate.

The fact of the matter is that the most important business decisions, and the fundamental practice of forecasting itself, are based primarily on backward-looking, after-the-fact, inward-looking data. This is why it’s no mystery that a majority of companies are dealing with 50% or greater error at the execution level of forecasting measured on an absolute basis. With this in mind, can you think of a better way to control business costs than to reduce forecasting error?

Besides improving the forecast platform, improved information would be the single most important tool for reducing forecasting error. If you could obtain more direct feedback from your customers (what they’re selling, what they have in inventory, how their latest promotion was performing) would that help your forecasting and planning? If your business is seasonal, would more accurate weather information help in your decision-making? If you supplied the residential construction market, would daily updates on housing starts have an impact? Does unemployment impact the consumption of high-end craft beers, and does this vary by region? Does overcapacity in the market among your competitors impact your profit margins? Do more than two or three external factors impact demand for your product at the same time?

Yup – we are going to have to talk more about this one. External data quality and timeliness, and then managing that information to optimize your decisions, will be the next frontier in business management. The good news is that Demand Foresight believes we have the platform, and there is now a great proliferation of more accurate information and competitive data markets available for more industries. Any input, experiences, examples, questions and critiques will be welcome.

What our forecasting and planning software can do.

Put up or shut up: The corporate guarantee

Posted on November 9, 2010 by Gene Tanski

By Gene Tanski, CEO, Demand Foresight

Things were getting heated at the sales meeting. The cause of my anger was an old theme: Industry-wide, client expectations for business software were so low that stories about the failure of big enterprise projects had practically become wallpaper.

Where were the repercussions for the business performance that never materialized? The big systems failed to deliver what they were supposed to over 70 percent of the time and the big checks just kept getting cut with no accountability. The whole dynamic needed to be nuked.

In the heat of our discussion about the institutionalized negligence of our gigantic competitors and how we could exploit it, a 25-year-old, Xbox-playing member of our team, said: “Dude, if we’re that bitchin’, why don’t we guarantee it?”

“What?” I asked him. “Are you nuts? Do you have any idea how software works?”

“No, not really. But I hear you guys constantly complaining about how everyone else over-promises and under-delivers. Why not do something about it?”

That simple dare became our biggest differentiator – and, more surprisingly, revolutionized the way we run our company.

During the dot-com boom, new businesses were founded on completely new thinking by young professionals, unencumbered by any notion of what was or wasn’t possible. Most of that potential was never realized, though – at least not in the first wave, since the young visionaries had no grounding in the disciplines that would sustain their visions over time.

However, we wondered, could our team fuse the experience of the old hands with the “anything is possible” optimism of our young teammate?

Once we got our minds around the concept, the experienced guys on the team were able to adjust some long-held assumptions and work through how to handle the risk, build the pricing and generally operationalize the concept.

It was a little bit like learning how to fly, as characterized by Douglas Adams in his “Hitchhiker’s Guide to the Galaxy” books: the key to flying was to throw yourself at the ground really hard, and miss.

It was exhilarating. I felt like we had just missed the ground by a huge margin, and instead were flying straight to a business model that embodied the exact opposite of everything we hated about the IT and consulting world.

The guarantee was an explicit one – with no wiggle room. Clients would measurably improve their business performance — in our instance, a 25 percent minimum reduction in absolute forecast error — or we wouldn’t get paid. Not a dime.

It could have been a disaster, but taking this leap of faith actually did incredible things for our organizational focus – and ultimately helped cement our culture and internally align all divisions of the company.

The developers know that the software has to work and be relevant to specific job responsibilities or they don’t get paid. Implementation and technical support? They better get it right or they don’t get paid. Sales people? They had better understand the client problem and know exactly how to solve it, or … well, you know…

Another benefit of this ‘put up or shut up’ philosophy was the elimination of the need to micromanage. Once everybody understood that the promise would not bend, I found I could trust everyone to solve problems the way they thought best.

Vacation policy? Didn’t need it. Our team was entrusted to take the time off that they knew they could afford to take. Office? Wherever they could open a laptop and do their best work. This culture tells us a lot about the kind of people we should hire — can they stay motivated and productive in our unique environment?

So an energetic, passionate clash of skilled professionals turned out to be lightning in a bottle. It let us fuse the brashness of youth with organizational know-how.

We still argue in meetings, of course. But these days I enjoy it. You never know what sorts of benefits it can produce.

This post first appeared on Venture Beat: Entrepreneur Corner on October 26, 2010

Industry Trends – Beer Distribution and Improving Profit Performance

Posted on August 31, 2010 by Gene Tanski

Beer Distribution is an interesting business: High margin, protected by regulation that has traditionally limited most forms of competition, which leads to an overall lack of incentive to innovate technologically.

Nevertheless, despite the lack of innovation incentives there are some activities occurring that signal the status quo may be changing a little bit; for example, the recent foray of Berkshire tossed into the mix through the purchase of a couple of distributors.

If the current dynamic were to change, for whatever reason, forecasting would be one area that would allow distributors to rapidly improve – even advance – their bottom line performance outcomes. Currently, on average, there is not a lot of focus on forecasting. Basic practices involve sales people “working” their on- and off-premise customers, while the inventory people make sure they keep enough stock on hand to ensure customer order fulfillment is met. Inventory managers look for opportunities to take advantage of strategically ordering from suppliers that game prices increases, etc.

A heightened focus on improving forecasting and ordering would allow distributors to lower working capital invested in inventory, while maintaining and/or improving customer service.

Customer service could improve in a number of ways; better order fulfillment being the most basic upgrade. On the more advanced side of the equation; distributors could work together with bars and liquor stores to make sure the products stocked, or on offer, respond and adapt to seasonal changes, trends, pricing, promotions, and holidays – making the distributor a value-added supplier.

In turn, the end merchant will become an even more valued customer by providing a more accurate forecast to their suppliers. This helps distributors and their supply chains become more efficient. Ultimately, this virtuous cycle helps set the distributor apart as a better supply partner – making it one that beer manufacturers will want to work with and which has the capacity to make a product successful in a new market. This allows the distributor to negotiate more favorable terms with suppliers, thereby increasing margin performance. Everyone benefits.

Improving the forecast model will require improvements in technology and process systems – something that owners will have to support. Since distribution sales people are singularly focused on driving volume and taking care of their customers, they do not take kindly to activities such as supply chain forecasting. But their input is critical in order to achieve a “big picture” point of view that will help the entire company. When forecasting is tied directly to how it will help sales people earn more money (working for a higher margin distributor), a critical component of improving forecasting will be realized.

POS data and beyond: will your forecasting capacity be outstripped by the data gusher?

Posted on June 23, 2010 by Gene Tanski

I had the pleasure of speaking with supply chain VP Noha Tohamy of Gartner/AMR Research recently. We were discussing exotic new taxonomies of demand forecasting and demand planning — demand sensing in particular, and where it fits within our understanding of the S&OP process. We also talked about the value of a holistic approach to demand planning — something we discussed earlier on this blog. Noha agreed with the Foresight premise that a complete, holistic approach to demand planning and forecasting was best: the ability to look at short, medium and long time frames at multiple levels of detail (store/customer to entire networks and everything in between) all at the same time. However, she highlighted a couple of critical caveats. One was the assumption that a company has a platform to enable such a comprehensive approach. Enough said there.

The other caveat is data. In some instances, forecasting and analytical computing ability exceeds the timeliness and accuracy of the data available; in others, there is more data available than some technologies, processes and personnel are capable of handling. Often both these scenarios can be found at the same company. Which problem do you tackle first? Or can you take them both on at once?

Putting POS data in play: a field example

Let’s get a bit more detailed. In terms of importance for improving supply chain efficiency and building partnerships with your customers, POS (point of sale) data ranks high. But it also serves as a good example of the conundrum expressed above.

More advanced platforms and better collaboration have given supply chain technology vendors the ability to grab POS data that is made available either directly by the retail stores or through aggregators such as VIP or IRI. This data is often made available on a weekly basis and aggregated at a chain/region level rather than by store. Historically, the reasons for this have been data size, network connections etc., but these reasons are becoming less relevant as technology improves.

For POS data, even the weekly schedule is frequent enough to allow demand planning applications to grab it and leverage it for modeling, inventory management, trend reporting, and more. In fact, these same applications would allow for the same manipulation and value to be derived from more timely POS — say, on a daily basis and at a store level — which would allow suppliers to more actively respond to trends such as overselling in response to a promotion. Demand Foresight brings its clients this capability, as do others such as Terra Technologies.

Wal-Mart and Home Depot: stunning implications

However, now groups like Wal-Mart and Home Depot are advancing an even more immediate data model. They are actively prototyping a business model wherein they do not take ownership of the product at their stores until the transaction at the cash register — basically a back-to-back where the retailer collects cash from the customer, only having “owned” the product for a fraction of a second, then paying the supplier of the product 30, 45 or 60 days later.

There are several ramifications for this model, but let’s focus on the potentially stunning impact in data alone. How many of you (and your companies that supply retailers, or supply companies that supply retailers) have platformed themselves to take in huge amounts of POS data once a day? Four times a day? Hourly? Fractions of an hour? Given the model described above and the facts that:

• You have responsibility for the product until it is actually sold
• You are still operating under service level agreements that demand coverage levels for each square foot of shelf space

Are you prepared? Most are not and this is an example of data overtaking technical capabilities.

Broadening the data question

And remember, this is just one type of data. What about data associated with capacity and the ability to promise orders? If a customer calls and requests 10,000 pieces of product X, can customer service respond immediately with all the applicable availability, time and requirement answers? What if your products have a short shelf life? These are all critical to your forecast.

What about external data such as weather? Planalytics — a great company run by some outstanding ex-Air Force badasses — provides highly accurate and detailed weather info. Some are using the data to help with seasonality and impact on big sales days such as 4th of July. Now companies can profitably tackle formerly esoteric questions such as “How much more beer will we sell if the temp is 100 instead of 80?”

But even all this only scratches the surface of the minute and critical indicators available within Planalytics’ functionality. There’s still demographics, raw material pricing, market capacity…the list is endless, but also critical to answer as these indicators provide huge value for forecast accuracy in the short, medium and long term. Few applications are set up to fully take advantage of everything offered. This is the essence of the data conundrum.

So which side of the problem do you attack first to impact revenue in a positive way? Ideally, both. It will ever be our position that a holistic approach that marries detail with high-level strategy and the very short term with the long term is always going to provide the most value to an enterprise and its bottom line performance.

However, I think professionals are best served by being honest with what they really have to work with and then building from there — so if POS data is available on a weekly basis and it is not being used, then focus on taking advantage of the POS; learn the possibilities and build from there (invest in the correct applications). If however, you and POS are old friends, then tackle the other side, start to invest for the future by following tracks laid by companies like Best Buy and Sony, who are executing complete and real-time data sharing. If you platform yourself correctly, not only can you get ahead of the data curve, but you’ll be armed with a unique competitive weapon: the ability to approach your retail customers and say, “I know how you can optimize the dollars generated from each square foot of your stores and distribution centers.”

Hmmm – helping each partner of your value chain maximize their efficiency and profitability…Now there is something that can positively impact your EBITDA both for the long term and in a way that allows for competitive differentiation- and all of it tied to a focus on improving forecasting and demand planning.