About Mike Doherty

Software Selection 101

Posted on November 20, 2012 by Mike Doherty

Here’s a recipe for disaster that we’ve seen all too often when it comes to selecting and implementing new planning systems:

Step 1: Survey people in the business to gather requirements

Step 2: Evaluate available software solutions against the requirements list and make a selection

Step 3: Design the future state processes

Step 4: Implement

On the face of it, it seems pretty logical and orderly, but there are some major flaws with this approach.

In Step 1, the business is being asked by a project team for their requirements, but what is the context? Most people in the day-to-day operations will see things through that lens. If you ask them what the requirements of the new planning system will be, they will likely ask for a mixture of:

– Functionality in the current system that they happen to like. In this case, you run the risk of selecting a system that is most similar to what they do today – how will that improve business results?

– A solution to a problem that is currently giving them pain. In this case, there’s a chance that important foundational requirements are not considered in favour of something that may be short term or temporary.

– Some cool things that they read about in a trade publication. In this case, you may put too much weight on “nice to haves” that aren’t really critical requirements.

Step 2 (selecting software to support the identified requirements list) makes perfect sense. However, the quality of the decision will only be as good as the identified requirements driving the decision (see above).

By the time you get to Step 3 (designing processes), the software has already been selected so you’re basically designing in a box. It’s at this point where you’ll start prototyping scenarios in the new system. You may soon realize that HOW the new system meets the original requirements may not be ideal. To avoid a backlash from the business, there will need to be some workarounds or even customization.

During the implementation (Step 4), you’ll continue to find things that don’t “fit”, requiring further workarounds and more time.

So how can these pitfalls be avoided?

By following the same steps, but in a different sequence.

Step 1: Design the future state processes

While people may be chomping at the bit to get moving, it’s our experience that taking sufficient time up front to align the organization saves a lot of time and aggravation during the build and implementation stages.

By taking the time to really think about what you want the future state to be (and before you do anything else), you can design freely and be guided by sound principles, rather than the constraints of the software you bought.

Step 2: Survey people in the business to gather requirements

A sound, unconstrained and principle-based process is one that’s also (by necessity) in plain English and easy to explain and understand.

With the basic process designed, discussions can be had with people in the business to make sure they understand what the new world will look like and the principles on which the design was based.

Only when people understand the future state vision can requirements to support that vision be flushed out.

Step 3: Evaluate available software solutions against the requirements list and make a selection

Because you’ve taken the time to get the desired future state designed on paper and had people develop requirements in that context, you can objectively evaluate software solutions based on their ability to enable that future state.

Because the design was unconstrained, you can be sure that you won’t get a perfect fit with any software package detected. But at least you know in advance what you’re looking for the software to do and can evaluate objectively. What’s more, you’ll have a good idea what kind of workarounds or compromises will be necessary before the final decision is even made.

Step 4: Implement

There will always be bumps in the road as you implement, but by taking time to think and educate the business up front, you can be confident that you didn’t miss anything critical and that the bumps will be small.

Performing the right steps is important. Following them in the correct sequence even more so.

Over Complicated

Posted on November 8, 2012 by Mike Doherty

Wiley E. Coyote is a super-genius whose sole purpose in life is to catch, and eat, the Roadrunner. With all the available resources of Acme Corporation at his disposal, you’d think the Roadrunner was doomed.It never seems to work out that way, however. Wiley E. Coyote is the victim of over-complication. His booby-traps and schemes are just too sophisticated for his own good. It’s over-complication that consistently lands Wiley E at the bottom of the canyon.I think we can learn a lot from Wiley E., especially when you think about what’s happening with respect to forecasting for the retail/CPG supply chain.

For decades people have been forecasting what should have been calculated. And since you went down that path, very logically I might add, you’ve had to add more and more complexity to account for the cornucopia of programs, formats and challenges that marketers, merchants and salespeople have dreamed up.

The result? Sophisticated algorithms and approaches to forecasting something that should never have been allowed into the forecasting engine. I find it both funny and quite sad to hear self-proclaimed supply chain experts beating their collective chests and telling everyone to use “downstream” POS data in their mathematical forecast models.

How exactly, Wiley E? The answer you normally get is nice and reassuring…”by using advanced analytics”. This kinda reminds me of another great cartoon character, Foghorn Leghorn…”I say, boy, it’s all too complicated for ya. Let me splain it to ya”.

Perhaps you’d be better served if you read and understood Dr. Joesph Orlicky’s startling and profound statement…”never forecast what you can calculate”. Joe made this statement in the 1970’s and it’s truer today than it was back then.

When it comes to retail/CPG forecasting, most of the experts are terribly misguided. Not only are they forecasting what should be calculated, but they’re pre-occupied with the wrong end of the supply chain. Why aren’t they talking about the retail store (or web portal, or markets) and speaking a common language…consumer demand. Real demand.

Why wouldn’t you just forecast by item by store and calculate the rest? Not only is that now possible, it also provides the most reliable forecast for all supply chain partners since all the variables are factored in, where they occur.

Plus, as an added bonus, you’ll get unprecedented visibility into your supply chain. Not what you have in inventory now and what’s on order. That’s chickenfeed. We’re talking about projected sales, receipts, inventory, capacity needs and so on.

Yup, when you only forecast where it counts, you get so much more. It’s like that extra cherry on top of the ice cream sundae!

But, you ask, “wouldn’t you need to be pretty sophisticated to forecast consumer demand at store level”?

The answer is: not really. You will need to recognize a selling pattern, trend, seasonality and flag past events and abnormal conditions. The beauty is that you’d be forecasting consumer demand, which has much fewer constraints and conditions attached to it.

Since the forecast is at store level, you will also need a way to predict and manage slow selling items – since retail is dominated by them. And the forecast shouldn’t produce small decimals for these types of products. Rather they need to produce integer-like forecasts that can then be calculated into the demand plans for the supplier of the store.

In addition, you’ll need a simple and effective way to update the forecast, in aggregate and then for each store, for things like promotions and/or market intelligence.

What about promotions? Surely they’ll need advanced analytics?

Years ago we tested it. We developed some causal forecasting equations and also let teams of experienced merchants and supply chain planners develop forecasts for a bunch of upcoming promotions.

The teams, on average, developed more accurate forecasts than the algorithms. Not only better forecasts but obviously more accountability in the forecasting process too.

What we found was that it was just too difficult to find math models to reliably explain all the inter-relatedness of expected demand. Yet, somehow, the teams could use historical information and their own judgment about the future, collaborate, and predict the future with reasonable accuracy.

It’s ironic. The farther away from consumer demand you are trying to forecast, the more constraints and difficult it is to do.

You have a choice.

You can try to forecast your way to greatness, or you can calculate your way.

RedPrairie acquires JDA

Posted on November 1, 2012 by Mike Doherty

In big news, RedPrairie will acquire JDA Software! If they get this right, and strategically select the best solutions for customers, then this could become a powerhouse in supply chain management solutions.

Shelf Connected Supply Chain

Posted on October 30, 2012 by Mike Doherty

Lots of recent press for what is now being hailed as The Shelf Connected Supply Chain. A excellent piece of research from Supply Chain Digest on how retailers and manufacturers view this game-changing approach, including what they see as barriers to overcome. Check out this excellent report by clicking here.

Of course, we all know that to make this a reality retailers and manufactuers will need to adopt and ingrain the Flowcasting process as their supply chain planning processes.

Mentally Separating Demand and Supply

Posted on September 20, 2012 by Mike Doherty

In order for the replenishment planning process to be as flexible as possible going into the future, it is imperative that a clear distinction be made between demand planning and supply planning.

The goal of the demand planning process is to predict behaviour of customers. Customer demand cannot be directly controlled and must be taken as given in the supply chain. We do our best to predict this behaviour and schedule resources (i.e. supply) as efficiently as possible to support the wants of customers. When we have our demand planning hats on, the furthest thing from our minds should be considering how this demand will be satisfied. Demand is demand, and it is not subject to constraints. This is what keeps the demand planning process as pure as possible.

Once you have a handle on your demand, proper supply decisions can be made to ensure that demand is satisfied. That’s the mental separation — demand is not within our scope of control and must be taken as given, while supply decisions can be made and remade in order to best satisfy changing demand patterns.

Optimize the order?!

Posted on August 10, 2012 by Mike Doherty

Huh? Why would you want to optimize the next order for a product? Instead why don’t you determine a series of planned orders, well out into the future and share those with your supply chain partners. And update these planned orders as things change (like sales, for example). That’s the ticket to improvement…for everyone!

In the immortal words of Kenny Banyon, “that’s gold Jerry…gold!!”

Searching

Posted on July 4, 2012 by Mike Doherty

“I hope to soon be in contact with the man who is searching for Noah’s ark.” – Jim Sullivan

It’s early June 1972 and my Mom would do something she’d regret for years. On my 10th birthday she gives me a wooden chess set and a chess book.

I devoured the book, studying the games of the great Jose Raul Capablanca. Then in September the world becomes fascinated with chess and with one Robert James Fischer. The Fischer – Spassky match gathered worldwide attention and put chess on the map in the west.

Fischer would become World Champion, then drop from existence for 20 years – never to play again until 1992. Bobby Fischer became a hero of mine and soon I announced to my parents that I intended to one day become World Chess Champion.

For a few years I was searching. Searching to become the next Fischer. Eventually I’d give up on my dream.

The point of my little personal ditty is that searching can be a dangerous and pointless thing. Especially when the search is fruitless.

Supply chain planners have been searching for lots of things too. One thing that many have been searching for is the optimal order.

Like my quest to become the next Fischer, this is a search that makes little sense.

What, exactly, is an “optimal order”? What criteria would you use to determine its optimality? Weight? Cube? Dollars (heaven forbid)?

What makes this search futile is the paradigm shift in retail planning systems and processes. It’s a fundamental shift that, on the surface, sounds like nothing when in fact it’s a big deal.

Retail planning will see a seismic shift from ordering to planning. For what seems like eternity retail supply chain planners have been worshiping at the altar of orders. A product is either on order or it’s not. Optimizing the next order was critical since that’s all replenishment cared about.

Today smart retailers understand that there is little value agonizing and fretting over the next order. Rather, they are beginning to understand that service and costs can be improved significantly not by focusing on the next order, but by carefully determining a series of planned orders – well into the future (like, say for the next 52 weeks).

These projections can be shared with the supply chain partners who are expected to satisfy these future orders. It makes their job easier and helps to ensure no surprises.

These order projections can also be used to determine future capacities, financial requirements and potential problems. Combined, these projections form a powerhouse of information to be used by everyone in the extended retail supply chain to deliver unheard of service levels, while simultaneously reducing total supply chain costs.

In a world of planned orders, what sense does an “optimal order” make? None, precisely.

That’s because in the new world each planned order is dependent on the previous ones. The planned orders adjust based on what’s happening at the store shelf, only for the upcoming one to become a committed order at the agreed-upon lead time. Trying to optimize this order at this stage could change all future orders.

Does that make any sense?

Why not build realistic and sensible ordering rules into your planned orders, then let actual sales fine tune the planned orders until they are ready to be committed? Wouldn’t that be much simpler, easier to understand and cause less disruption than searching for the optimal order?

Soon retail supply chain planners will realize that searching for the optimal order is pointless.

The same conclusion I arrived at in my search to become the next Bobby Fischer!