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The joy of updating old coding gems

September 28

As software developers, we all dream of writing perfect code. A piece of code that still works after 20 years and is still actively in use. Here at OMP, we have some absolute coding gems. But the passage of time is cruel and, as code gets covered in layers of dust, you may... Read blog the joy of updating old coding gems blog-yes as software developers we all dream writing perfect code a piece that still works after 20 years and is actively in use here at omp have some absolute but passage time cruel gets covered layers dust you may need to do an update that&rsquo s when find out if you&rsquo re dealing with real diamond or fake very elegant reporting module was one such gem it could take any data carry deft transformations outputting new table-like structure be visualized ui wrote this about 25 ago more accurately my colleagues &mdash i not enough legally working back then netscape popular computers had hard drives no than couple gigabytes for complete system &nbsp requirements legacy state-of-the-art went by added lot other functionality our application including better pivots chart views longer useful graphical reports did become important cornerstone interfacing applications because interfaces run during night how well performed wasn&rsquo t anymore feeding into calculation times began stretch several minutes later hours even faster didn&rsquo care ran those nights were long arrival got&nbsp reused making interactive result its performance became much before assigned job program who wants wait pressing button from pure c latest c++ standard what pieces read blog can your concurrent planning response scheduling cycles supply consumer packaged goods centralized guess what: shocked looked being familiar latest&nbsp used seeing vectors unique pointers lambdas algorithms instead relic barely been touched last was&nbsp using constructs now avoid modern programming problem hand needed modernized without risk introducing issues just too great diving recognized concepts replaced equivalent made smaller readable saving cpu vector tested every stage reproduced scenario completed under something sounds good true it&rsquo often shatter realizing own investigation consulted finally concluding everything worked should disbelief dissecting changes understand exactly happened compared profiles which identified specific revealing main contributor introduction technical terms c-style arrays type these reallocated single pushback however element amortized constant convinced right thing took look understood make minor additional further reduce computing acceptable two keep their sparkle so improved 99% polishing easier maintain resulted work people developed primary school will tell write today ends up hope day onlooker successors yet alive looks over 2021 recognizes beauty becomes outmoded isn&rsquo garbage history deliver value customers would like details get touch

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How a love for mathematics brought me to OMP

September 6

I haven’t always loved math. At school, my interest (and my grades) fluctuated with how engaging my current math teacher was. If a teacher didn’t have a passion for explaining the fundamental concepts and instead handed us formulas and equations... Read blog love for mathematics how a brought me to omp blog-yes i haven&rsquo t always loved math at school my interest and grades fluctuated with engaging current teacher was if didn&rsquo have passion explaining the fundamental concepts instead handed us formulas equations like they fell from sky would mentally check out do only minimal of work required pass spend lessons passing notes friends &nbsp isn&rsquo just tool applications are endless read blog find we put science in your supply chain luck that had truly excellent final two years high our first lesson she asked what point answered other natural sciences this met by scoff reply end convince wasn&rsquo but&nbsp &ldquo queen all sciences&rdquo did: took time teach background any calculation were working on offered intuitive explanations proofs gave peek inside could be it&rsquo s because these decided study university doing incredible things over next few discovered is everywhere mathematical tools can used researcher using models calculate best placement windmills ensure least impact local endangered bat populations another optimization develop medical prosthetics group investigate leukemia attacks immune system got opportunity apply skills learned lectures help estimate parameters chemical experiments calculating optimal routes parcel delivery every problem underlying many &lsquo real life&rsquo challenges there abstract problems especially true planning question schedule sequence jobs reduce overall machine set-up traveling salesman intensively studied academia issue move volumes product through there&rsquo network flow ways solving logistical issues figuring vans found journals day no power match! after seeing ready leave world felt sure lot opportunities industry it must get use almost company&rsquo homepage advertises ai-powered technologies soon however says box what&rsquo interviews ask type methods whether company kept up research often hums haws confessions don&rsquo really here&rdquo algorithmic hardly ever done or outsourced while one large said guy who developed algorithm ago&rdquo became pretty crestfallen nobody outside see great putting interview already tell different whole team people devoted developing improving solvers -- solver --&nbsp strong academic ties backing theses scientific solve customers&rsquo core their business model rather than being relegated sidelines own lp / mip crying loud immediately knew place i&rsquo ve been here now able so much diverse array real-life also chance keep learning new example following course slogan designed make look smart promise we&rsquo re committed reason chose you passionate about too chains join

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Why master data should not be the victim of maternal gatekeeping

August 2

Ever heard of maternal gatekeeping? It’s the term invented for that feeling that a mother tends to have: ‘no one can take care of my child the way I do’. The cliché goes that mothers are inclined to give babysitters five... Read blog

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The 5 essentials of a good forecasting blind test

July 8

How do you know if a forecasting solution will perform well? There are many available on the market using a wide range of technologies, but which would be best for a particular industry or company? Well, the proof of the pudding is in the eating.... Read blog the 5 essentials of a good forecasting blind test blog-yes how do you know if solution will perform well there are many available on market using wide range technologies but which would be best for particular industry or company proof pudding is in eating that&rsquo s why companies get providers to submit great tests need carefully organized want learn anything from them five essential requirements test: 1 sure make it really data used testing consists collection time series product-market combinations example skus per country also include training making forecast and that predicted let&rsquo assume have three participants provide sales history january 2016 december 2020 ask 2021 june no participant given access because allow tweak information unavailable real circumstances should not revealed anyone prior even trusted scientists could inadvertently introduce some kind leakage leading unrealistic results planning department 2 sufficient number items someone an expert poker player answer must based more than they play just one two hands same goes too influenced by coincidence carried out only handful i always recommend providing set at least several hundred thousands this has advantage leaving little room any manual manipulation automatic capability before human looks &nbsp 3 period long enough avoid solutions underperforming overperforming therefore reusing above preferably asked competitors actuals wouldn&rsquo t complete picture solution&rsquo performance when assessing accuracy specific lag &lsquo month+1&rsquo organizing multiple rounds case outlined mean following: february march so may look cumbersome indeed provided all immediately anymore intentional unintentional cheating 4 share your evaluation metrics upfront organizers reluctant reveal evaluate different forecasts seem fair we give their best&rsquo whatever method however common practice competitions shared like comparison with car racing teams finetune car&rsquo engine transmission suspension tires etc each race track&rsquo properties allowing its engines similar cars tuned challenge hand algorithms adjusted optimize kpi such as mse mape mad bias weighted combination kpis granularity months weeks days calculated month+1 month+2 precise tuning depends stated expectations thus customer equal insight into along over among independently verify guarantees transparency objectivity does involve disclosure intellectual property relating were generated organize interpret use feel free reach touch

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The 5 key elements of successful remote supply chain projects

June 30

After more than a year of lockdowns, face masks, and social distancing, I still don’t know what I long for the most: getting back my normal private life or resuming work as it was before the pandemic. I manage digital... Read blog the 5 key elements of successful remote supply chain projects blog-yes after more than a year lockdowns face masks and social distancing i still don&rsquo t know what long for most: getting back my normal private life or resuming work as it was before pandemic manage digital transformation worried that covid-19 would muddy waters ongoing how workshops training sessions out could acceptance tests dry runs go-lives be in full lockdown while this new reality looked if we our customers completely reinvented way working together but discussed with colleagues concluded basically matter applying good practices we&rsquo ve been advocating many years although sometimes did stringently fresh touch ingenuity so i&rsquo m happy to share you found success why they will crucial post-covid-19 era &nbsp 1 stringent formalized project management apparatus normally some insist on site very large team at critical stages implementation colleague aditya karnik example managed strategic over 2 chemical company scheduled completed 2020 involving an integrated about 100 people including company&rsquo s staff march suddenly faced fact almost nobody allowed anymore yet postponing not option because there were clear targets reducing inventory huge impact cash flow buffers demand disruptions inducing additional risks building excessive stocks read blog find planning continued compensated lack onsite presence by being much stricter activities planned greater detail clearly listing prerequisites responsibilities actions expected results all meetings other decision-making became formal too: signing off less decisions nod can circumstances engenders frustrations have only virtual post-go-live elaborate small teams focusing limited sets functionalities approach actually works point where several are now insistent having christophe ourliac said: &ldquo businesses latin america used require us least 70% positive experience assistance lead modest probably around 50% &rdquo increased effort documentation crisis established practice update end remotely changed communication increasingly important everyone understand heading agree which features implemented everyday one adapted process place providing status information minor documented from onset take away business leaders also systematically deployed mantis issue tracking system customer had reluctant use such book advantages clear: issues reported quickly depth resolved rapidly 3 organize covid-19-proof initiatives close encounters makes difficult members get each build strong spirit omp ways successfully integrate number newly hired into different development advisory situation inspired creative: hosted breakfasts lunches coffee breaks organized home office quizzes hours set up lunchtime walks worldwide allowing meet groups compliance local covid regulations similar things it&rsquo solid mix meeting types daily standups underestimate importance informal who manages brazil says cultural thing: essential discuss latest football soccer game hand 4 involve protecting work-life balance trust is especially teambuilding typical diverse juniors seniors newcomers experienced backgrounds even thousands miles priorities households may young families requiring attention times day bringing challenges said me first two weeks felt like break soon hard combine running family taking care top priority continue when need protect too themselves lot responsibility give them online express helps confidence steerco assume active encouraging role never given managers reassurance these strange steering committee should play leading suggested falling waterfall methodology allow easily sprint another proposed plan b involved compensating delayed go-live functional capability upgrade jasper wouters pointed supportive attitude deserved big thank difference takes facilitate without compromising result want part action join global manager see open positions

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How to ensure that your digital supply chain transformation creates value

June 10

As a supply chain expert, I’m often asked “How can I be sure that my digital supply chain transformation will have a positive impact on my company?” Usually, this happens during a coffee break or a networking dinner. So,... Read blog create value with digital supply chain transformation how to ensure that your creates blog-yes as a expert i&rsquo m often asked &ldquo can i be sure my will have positive impact on company &rdquo usually this happens during coffee break or networking dinner so putting pen paper share insights in brief blog post &nbsp overdeliver overpromise you read the answer here bullwhip effect planning scenarios forecasting uncertain times collaborative forecast accuracy why does question pop up frequently business leaders juggle budgets and priorities every year many of them see project which put significant load their teams they want returns that&rsquo s initiatives are accompanied by a&nbsp preliminary case outline listing costs expected benefits strictly financial terms may also for example rely reducing inventory levels accelerating throughputs &ndash goals quantified measured pretty easily but approach results rather modest ambitions only limited company&rsquo overall performance resilience fact numbers very conservative because it feels more comfortable less risky than result could cast doubt whether is going make real difference adding qualitative equation experience exclusive focus quantifiable tends cloud weaknesses process reduces effort game math think about volume planners losing lot valuable time collecting data information who need crucial decisions based just gut feelings changing demand faltering hot topics pandemic traditionally leads optimize plan division at risk colleagues upstream downstream firefighting mode big then boils down including such visibility quality decision making employee satisfaction engagement ability willingness all across work together benefit whole true what you&rsquo re trying achieve eventually should quantitative kpis identifying pain points improvement opportunities inevitably to&nbsp scrutinizing reshaping organizational processes some&nbsp might back away from challenge yet convinced it&rsquo way go would certainly recommend upgrade strengthen beginning engaging executives sponsors well managers extended input help organization better identify along prioritize multiple dimensions actions included set program continuous monitoring remains priority everyone involved brings much bigger return end written ensuring impacts d happy talk through person soon hope did story trigger curiosity feel free contact me get touch

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The importance of crashing early

June 3

Some fellow software developers argue that a software crash is an indication of poorly written or unreliable code. It’s a popular notion, but I think it’s a fairly common misconception. Crashing can actually be very useful in software development. Don’t get me wrong.... Read blog the importance of crashing early blog-yes some fellow software developers argue that a crash is an indication poorly written or unreliable code it&rsquo s popular notion but i think fairly common misconception can actually be very useful in development don&rsquo t get me wrong systematic error handling essential any piece and it vital those running high-uptime devices systems you&rsquo re not likely to agree surgical operation if you know cardiac monitor used procedure has tendency stop functioning once while without warning similarly authorities aren&rsquo going allow driverless cars on roads unless they&rsquo quite sure won&rsquo end up undefined state there&rsquo little discussion event failure such should do everything possible at least signal problem bring vehicle safe halt people then make their own decisions about its safety &nbsp catch &lsquo em all your complex represent special category meet stringent requirements yet many among them even engineers need all&rsquo sometimes aptly called pok&eacute mon anti pattern&rsquo universally valid really there are two reasons why first every single exception unnecessarily hard deal with let&rsquo take simple example: what cases we assume will never happen pointertype somepointer = dosomethingthatreturnssomepointer !somepointer // return thus nothing ignore ability read blog find out coding writing engineering developer engineer debugging important this something i&rsquo ve seen times &mdash assumes so writes form essence just ignores facts carries reason for doing satisfy desire handle assumption was could example due changes function because properly thought leaves as much chance behavior were checked returned variable left 0 causing division by pointer being initialized later endless loop set correctly user action looks like worked did would programming facebook accidentally overwrote relationship status complicated try explain life partner &hellip how trying cover path well point where start question whether say part critical system service errors exceptions per se instead use assert statements assumptions explicit easier understand new see shorter more than earlier demonstrates other leaving better fit humans closer cause depending type program immediately debug possibly production stated &ldquo happen&rdquo failed indicating also from trouble input data doesn&rsquo expectations indeed run into paths mentioned fact unexpected areas illustrates second allowing useful: facilitates process general fail fast slow correct both needed related further adding avoid corruptions afraid high list options contrary most soft way dogma certain circumstances good right away when ordinary happens business shouldn&rsquo here unlike real save care share thoughts touch

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Model the cause, not the effect

May 20

A joker on the internet recently came up with a creative solution to that old which-one-came-first riddle. “I ordered a chicken and an egg from Amazon,” he said. “I’ll let you know which came first.” Do I wish my life were as simple as that? No, I actually enjoy identifying... Read blog

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Machine learning is great, but is it going to crush statistical forecasting?

May 3

Machine learning is the talk of the town but is it going to crush statistical forecasting completely? The recent success of machine learning in the M5 competition has inspired some... Read blog machine learning is great but it going to crush statistical forecasting blog-yes the talk of town completely recent success in m5 competition has inspired some commentators predict death i think they are cutting corners while rightfully claiming its place demand there good reasons believe that even many years from now will be used conjunction with as a complementary rather than substitute technique here&rsquo s why &nbsp forecasting: extrapolating well-defined set data let me first briefly summarize principles technology all about using techniques such regression sampling and hypothesis testing on historical time series sales allows trends seasonal patterns correlations external factors identified extrapolated based assumption past behavior best predictor future frequently holt-winters model for example essentially extrapolates average values cyclical figure below illustrates what does showing blue red here’s supply chain planning neural network you don&rsquo t need master&rsquo degree statistics understand covid-19 pandemic severely disturbed 2020 into 2021 which undermines their predictive value forecasters apply several additional smooth out or otherwise adjust before them compute forecast ml solve problem not at just like uses including where was undermined by virus old gigo principle garbage applies much learning: identifying broader range use these different way presents opportunities put simply links inputs outputs there&rsquo no define equation upfront feed huge amounts carefully selected input output perhaps shipment large number products intervals then identify linked this so-called phase during trained &lsquo wires&rsquo immediately highlights one biggest appeals ml: can relatively easily almost modeling effort add same product family master calendar promotional orders point-of-sale weather economic identifies somewhat ingenuously if you&rsquo re feeding right make smarter over downsides mean end have suggested after ml&rsquo so fast only particular dataset we&rsquo sure winning models would also work well other datasets example: lot yet long history limited portfolio simpler probably still your bet heavier computational requirements take days train specialized hardware inherently less transparent more black box rarely big might resistance organization adopting because explained most importantly always guaranteed lead better accuracy adage valid: often cases simple moving provide fancy complement each potential guarantee naive machines sometimes see none vulnerable disrupted it&rsquo very likely come neither do without human intelligence that&rsquo another story want know how help! get touch

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The people behind the screens of the OMP Conference

April 15

Goodbye Miami, hello home office It's been just over a month since our first-ever virtual OMP Conference. An event that would have taken place in sunny, exotic Miami were it not for this nasty virus that’s been canceling all our plans for over a... Read blog people behind the screens of omp conference blog-yes goodbye miami hello home office it's been just over a month since our first-ever virtual an event that would have taken place in sunny exotic were it not for this nasty virus that&rsquo s canceling all plans year now and let&rsquo be honest everyone is sick tired these remote meetings seemingly endless zoom calls online teambuilding activities it&rsquo same when i joined omp&rsquo communications team last december was immediately involved organizing first right from start clear whether colleague or customer passionately committed to making work as newbie company great way learn while tech human aspect always prevails &nbsp building community being organization had front-row seat witnessing how builds real partnerships with customers some even turn into friendships turns out asked metals industry attending if he willing provide us testimonial afterwards answered: &ldquo will my pleasure help you friend paul vanvuchelen &rdquo made me smile find attached picture him director solutions enjoying nice cold drink together brella platform hosting allowed share ideas discuss trends experiences talk about their success stories challenges colleagues pointed type one-on-one networking more efficient than walking around chatting strangers at in-person but already said real-life interaction simply provides deeper connection understanding makes easier respond facial expressions body language also so much get away witty ironic remark keeping fingers on pulse read blog experienced united unison planning supply chain innovation collaboration helping prepare presentations learned project teams kept throughout disruptive many other things go-lives go ahead completely virtually easy most important lesson successful we each overcome hurdles aside attentive follow-up careful documentation good spirit between built core values mutual respect trust preparing future attempt combat fatigue during combined prerecorded live philip vervloesem senior vice president business development jan snoeckx associate product design presentation they maya audience otherwise empty auditorium talking what can expect near tried bring keep attendees going remember example sharing next-generation user experience cognitive reasoning models started pink elephant experiment simple invite think least 30 seconds looked smiled because course both thinking large animal although following offices probably reaction still felt bit strange couldn&rsquo t exchange knowing glance rest invited interact responding questions giving opinions seeing participate answers appearing screen jan&rsquo engaging end launched final poll asking participants say one word theme meant them cloud grew gratifying see biggest emerge therefore popular choice collaboration&rdquo best worlds indicated liked format there no need travel survey after clearly revealed prefer face-to-face conferences co-organizers told missed characteristic atmosphere events feeling world demos finishing up reception something myself come proud part worked &lsquo control room&rsquo head technical issues every meeting don&rsquo tell never anyone un-mute 700 registrants definitely exceeded expectations testimonials councils months enriching confirmed working heart passionate next look like who knows whatever &mdash hybrid forward fully experiencing sense aftermovie taste went

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How President Biden is challenging and encouraging supply chain leaders

March 30

As an advisor, my ears shot up when I tuned in to the TV a few weeks ago to hear our new president in the US, President Biden, talking about supply chain. His address marked the signing of an ambitious executive order on... Read blog

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What dating apps and supply chain solvers have in common

February 8

At conferences, my colleague Kris talks a lot about dating. Before you come away with the wrong impression, he’s not a professional dating guru and he doesn’t give out tips. Kris is one of the heads of OMP’s optimization department. His point is... Read blog dating apps and supply chain solvers what have in common blog-yes at conferences my colleague kris talks a lot about before you come away with the wrong impression he&rsquo s not professional guru he doesn&rsquo t give out tips is one of heads omp&rsquo optimization department his point smart solutions making them understandable for users pursuit now commonly known as xai uses analogies takes deployment planning solver an example this assigns stock volumes to demand incorporating range constraints kpis by using specialists call &lsquo weighted greedy fractional matching algorithm ' may sound either very complicated boring or both but underlying mechanisms that make work are pretty simple much more tantalizing subject online explain it audience its simplest form &nbsp imagine female male analogy goes like you&rsquo re building app your aren&rsquo so looking partner they just want fulfill their annual date requirements none lgbtq let&rsquo say women men because #feminism means instead 52 tons we&rsquo jane who wants keep existential loneliness bay having dates year 4 paul only each single has certain preferences when comes potential these could be shared interests appreciation same kind humor similar tastes night movies correspond such transportation costs difference between due availability among many others pairs how alike read blog understand from perspective easily explained first thing do calculate well possible pair fits together take sum over all preference characteristics instance important her can laugh rather than also likes political thrillers higher weighting calculation gives value match representing good fit would percentage on okcupid then sort matches way down list start best oliver bouldering comedian daniel sloss time 15 considers almost calling hobby oliver&rsquo get assigned no we ignore other pairings sorry girls there&rsquo enough go around still need remaining 37 she game moving second-best it&rsquo kate five william 45 william&rsquo excluded rest understanding logic prerequisite trust third-best case happy every saturday &mdash continue until men&rsquo given women&rsquo been satisfied works exact finding values quantities sorting working metaphor easy see really allows step user results if were eager deploy data science machine learning curious our browse through faqs submit own question learn

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OMP to the rescue: when COVID-19 knocks out an entire planning department

January 20

“When sorrows come, they come not single spies, but in battalions!” says Claudius in Shakespeare’s Hamlet, as his world collapses around him. He was musing about how, when bad things happen, they don’t happen in... Read blog

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Write code like music and drink medovukha

December 20, 2020

One of the rare joys of being a software developer is having the opportunity to work closely with people who live in remote parts of the world. Even building friendships with them. And then one day you find out that in that remote place they have... Read blog

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How happy numbers can spice up a programmer’s job interview

December 15, 2020

Imagine you’re in a spaceship being hunted down by co-workers who’ve been taken over by an evil force. The only way to open the lock to the safe area of the ship is by finding a set of happy primes. This is exactly what... Read blog programmers job interview how happy numbers can spice up a programmer’s blog-yes imagine you&rsquo re in spaceship being hunted down by co-workers who&rsquo ve been taken over an evil force the only way to open lock safe area of ship is finding set primes this exactly what happened main character sci-fi tv series dr who we all know prime number and there are numerous algorithms determine whether but well term &ldquo number&rdquo comes from world recreational mathematics it even has its own wikipedia page definition actually very simple: start with n take digits square them add together then repeat operation on result if repeated execution ends 1 called results endless loop unhappy or sad &nbsp wrong for two reasons at you might get question like: write algorithm should return true it&rsquo s false unhappy&rdquo let&rsquo try solve problem getting seems easy be tempted like this: char buffer 3 sprintf %d&rdquo size_t sum = 0 *buffer + code deceptively simple reasons: incorrectly assumes that numeric value equal digit not &lsquo 0&rsquo ascii 0x30 which clearly isn&rsquo t zero consists 2 when original would have between 10 99&rsquo no guarantee intermediate values remain smaller than 100 look mom so lesson #1 be: dealing information use easy: just modulo-10 one perform integer divide-by-10 while looping auto size_t{0} { remainder number%10 += * /= } function needed check using vector next step until reach wrap calculation above calculate final algorithm: ishappy int number!=1 wait do happens right will never terminate what&rsquo missing already encountered before most obvious keep std::vector every iteration continue extending interviewer ask alternative ways recurring std::set more efficient std::bitset fastest possible implementation extend show really thinking outside box bound learned textbooks example propose returns million could good opportunity your knowledge multi-threading too spaceships still lot fun okay was ever need kind real life probably lots other problems come solving important work innovative software company omp don&rsquo build our haven&rsquo always looking people spark creativity key real-life keeping discover engineering jobs join us! programming development out-of-the-box

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Dustin Johnson’s caddy and the crisis of historical data

November 20, 2020

Many of you will have watched how Dustin Johnson won his first Masters title last Sunday. As usual, nerves of steel were needed to make it through that final round and become part of history. And the course looked amazing again, despite the absence... Read blog

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How consumer goods leaders are successfully making planning cycles shorter

November 15, 2020

An increasing number of consumer goods companies are engaging in efforts to make planning cycles much shorter. But this ambitious undertaking comes with a great many challenges, obliging companies to redefine their... Read blog consumer goods leaders making planning cycles shorter how are successfully blog-yes an increasing number of companies engaging in efforts to make much but this ambitious undertaking comes with a great many challenges obliging redefine their as well the systems they use at beginning covid-19 crisis we all saw it took industry nearly two weeks replenish grocery store shelves products such toilet paper pasta and canned tomatoes which had been subject customer stockpiling delay wasn&rsquo t by chance these have average 10-day lead time significant part is due cycle running over full week &nbsp towards more responsive supply process packaged cpg discover that come concurrent response scheduling centralized good news investing dramatically shorten times putting place new production equipment allow quicker changeovers schedules dynamic also paves way for ambition move from weekly daily cycle&nbsp some cases even one per shop floor shift major change leading reorganize organizations completely seeing dissolve local teams favor service centers put devise optimize distribution deployment plans multiple manufacturing sites different parts world don&rsquo waste your or money reality provides perfect opportunity align further strengthen practices however means be tightly integrated historically used whole range best-of-breed solutions plan ordering while can work becomes almost impossible when you schedule every day each created constraints should apparent real smart solvers rapidly balance there&rsquo s simply no planners across value chain wasted on suboptimal solution understand single fully comprehensive how-to knowledge relating specific floors within unified being trained operational strategies plant serve solver techniques configured sure optimized company-wide stream perspective eliminating any subjective bias maintaining effective communication lines aware pulling away units could its downside too concern must always tune what happens between hub so valuable experience plants captured agreements define trade-offs made there conflicting priorities video conferences review deviation want learn manage check omp&rsquo omp

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Supply chain planning language for robots (and humans)

November 9, 2020

The world of supply chain planning sometimes appears to us as a vast, ever-changing field of knowledge, with new concepts being introduced constantly. Recent additions to the vocabulary are terms like ‘telescopic digital twin’, ‘agile planning’,... Read blog supply chain planning language for robots and humans blog-yes the world of sometimes appears to us as a vast ever-changing field knowledge with new concepts being introduced constantly recent additions vocabulary are terms like &lsquo telescopic digital twin&rsquo agile planning&rsquo resilient xai&rsquo but what do they mean mathematician i&rsquo m big fan clear definitions simple examples illustrate complex that&rsquo s ll try here first thing that should probably be clarified is none these refer any specific technology there isn&rsquo t one single algorithm behind xai example or generates rather seen underlying philosophies when it comes choice design technologies &nbsp twin so let&rsquo say you building robot sidekick help manage your after you&rsquo ve given cute face little wheels roll around on good friend&rsquo name ann might explain looks going need gartner defines this following: &ldquo representation physical can used create plans make decisions&rdquo * means inside mighty brain re construct mental image including all plants machines transport lanes well detailing how interact fit together zooming in out an read blog find explainable artificial intelligence makes if equipped she put information into context asking her opinion whether open plant pawnee indiana will then able look at picture&rdquo decision sense than getting caught up details similarly making decisions more detailed level sequence tasks machine day allows zoom relevant practice omp done by modeling using multiple interlinking twins corresponding different layers decision-making scopes adapting itself also always needs see changes puts it: must synchronized real just model &rdquo ties concept agility refers easily picked tell adding don&rsquo want say: hold wasn&rsquo explained layout me could please whole again instead quickly adapt some systems take even further allowing system dynamically detect inaccuracies suggest appropriate our&nbsp continuous data improvement&nbsp track called genie adapts accurately uses learning techniques calculate change rates based production avoiding disruptions now knows suggestions equip smart solver algorithms ai designed such way unexpected have massive effect resulting plan our basically sure too skittish doesn&rsquo completely overhaul once something happens achieved combination forecasting analysis methods predict place buffers dampen their effects understand has computed optimal - tells wonder got conclusion ask reply cause trust where acronym idea advanced come set tools allow them themselves putting abstract calculations back shows interconnected ideas work aware scope therefore each kept mind designing effective deserve robin batman kitt knight rider leslie future explore road map innovation insight 16 october 2020 tim payne

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The role of XAI in supply chain

October 26, 2020

How can people learn to trust the systems that are supposed to make their lives easier? That was one of the big issues discussed at the recent 'Smart People in the Smart Supply Chain' virtual conference hosted by Vlerick Business School in partnership with OMP, bluecrux and... Read blog the role of xai in supply chain blog-yes how can people learn to trust systems that are supposed make their lives easier was one big issues discussed at recent 'smart smart chain' virtual conference hosted by vlerick business school partnership with omp bluecrux and lineas experts from all over world dialed for an afternoon talks workshops presented leading voices both academia industry overarching topic 4 0 &mdash or technologies like ai other sophisticated algorithms be harnessed shape future planning &nbsp humans machines human-machine is a very important issue its most benign distrust leads avoidance sector this might result reluctance implement new destructive generate aversion even fear these really helping us they about steal our jobs read blog find out explainable artificial intelligence solvers talk entitled &ldquo we trust&rdquo professor karlien vanderheyden cristina danila janssen pharmaceutica conjectured lack caused combination three aspects: human factors such as users having unclear expectations system machine transparency what do contextual arising insufficient poor management communication eliminate it&rsquo s clear have figure let explain themselves ways understand appreciate ann vereecke ghent university kris dockx referred concept answer challenge according consists set tools techniques help not only but also interpret recommendations were made model &rdquo does work then went on demonstrate brings life consultants use three-step approach getting end complex solver behind automatic optimization plans: first step explaining algorithm works theory because procedures assign stock demand sound quite dry boring explanation more engaging achieved comparing it something everyone finds way interesting case online dating so instead assigning based abstract kpis explains through device lonely men single women hair color preference two practice user sees every move makes why video animation being able correct when wrong told which moves dislike learns take into account next time therefore becomes intuitively understandable controllable relationship between happy any things essential: understanding best relationships worked will look explore road map

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Why shorter scheduling cycles will become the new normal in consumer goods

October 20, 2020

An increasing number of consumer goods companies are gradually moving from weekly to daily supply planning cycles. Some have even managed to bring the cycle down to a time span of just one shop floor shift. The chances... Read blog shorter scheduling cycles in consumer goods why will become the new normal blog-yes an increasing number of companies are gradually moving from weekly to daily supply planning some have even managed bring cycle down a time span just one shop floor shift chances that this for chain value creation &nbsp we all know historically packaged cpg has always been on schedule at beginning planners create unconstrained distribution plan then update production so constrained can be deployed find out blog concurrent response is pragmatic solution manufacturing point view giving manageable workload disruptions during rest week ignored or best addressed by manually adapting bulk plans subsequent finished schedules and traditional scheme far optimal demand perspective however because it might take more than producers adjust their respond sudden changes don&rsquo t need covid-19 crisis understand could problem highly competitive promotion-driven market averting undesired knock-on effects technical organizational constraints helped keep practice alive example based dc stockouts tricky burdensome move if separate systems used processes also subject complex interdependencies such as availability dedicated tanks silos lot sizes components materials use shared resources phase-in phase-out dynamics campaigning changeover optimization means quick-and-dirty would inevitably lead upstream downstream parallel avert outcomes urged stock but markets forcing industry think financial considerations require manufacturers reduce safety stocks closely linked responsiveness consider company with $50 billion annual sales volume 45% average variation forecast 99% target service level operation reserved activities up 10 days additional physical 10-day time&mdash about $2 3 see graph agile operational around $1 5 reducing working capital much $0 8 making there&rsquo s no wonder reorganizing recent years allow responsive they&rsquo ve investing make equipment flexible process integrated present most omp implementation projects shortening day single least plants i expect evolution continue under pressure growing competition help smarter faster better forecasting solutions it&rsquo real paradigm which comes challenges organization must adapt work reengineered leaders tomorrow today already clearing these hurdles want learn trend towards check

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The rules of the planning game are changing – and that’s good news

September 25, 2020

Vlerick Business School recently issued a research paper – which you can download here – describing the future of planning and planners. The interviews conducted for the research took place before COVID-19, though it’s... Read blog rules of planning game are changing the – and that’s good news blog-yes vlerick business school recently issued a research paper &ndash which you can download here describing future planners interviews conducted for took place before covid-19 though it&rsquo s striking that many themes conclusions sync up very well with today&rsquo primary challenges example need more agile response to change predict shape demand in an autonomous closed-loop process common target increasing supply chain resilience looks bright anyone involved find out this blog digital planner collaboration not only will they have access systems run much integrated way these also bring significant steps further automating repetitive tasks while giving full control i like because it raises substantial arguments call action solution providers industry consulting firms require power continuously drive management improvements through technology talent particularly appreciate balanced approach discusses how traditional cascade activities become disrupted talks deeply about human aspect vision end is goal but means actually help do their jobs what most let me share some insights &nbsp 1 flows information cascading decision-making remain be highly automated now does mean exactly today companies work centralized facing costly challenge interconnecting those facilitating exchange between them there two ways overcome we move one overarching system contains all tried failed erp alternatively look efficient connect separate mentions experts aligned my opinion or building open closed build cover any type within single enables us use intelligence available going across operational strategic next allow seamless low-cost interaction other such as manufacturing execution 2 getting requires quality data know saying &lsquo garbage out&rsquo doing over past few years plenty invested amount manpower improve maintain however return on investment has been limited sure was limiting factor cases wasn&rsquo t used its potential due resistance just think hard implement abc-classification so what&rsquo changed starters recent advances ai ml created new appetite comprehensive solutions based big techniques processing huge amounts smart addition data-driven analysis provides organizations better insight into bias that&rsquo 3 go beyond number-crunching taking ownership mission really love portrays someone providing managerial support optimize profitability plant&rsquo touches at essence mission: ensure optimal material same time enterprise assets being best possible fulfilling market needs support&rsquo materialize when able deliver plan hope enjoy reading did message optimism opportunity feel happy hear your thoughts

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Are you ready for bumpy planning times ahead?

September 17, 2020

“We plan, God laughs,” is an old Yiddish saying that most supply chain planners would find mildly funny these days. Uncertainty is part of every supply chain, yet the COVID-19 outbreak brings that uncertainty in both demand and supply to... Read blog bumpy planning times are you ready for ahead blog-yes &ldquo we plan god laughs &rdquo is an old yiddish saying that most supply chain planners&nbsp would find mildly funny these days uncertainty part of every yet the covid-19 outbreak&nbsp brings in both demand and to spectacular levels what current situation how it going unfold traditional forecasting techniques will be less accurate than they used can done about &nbsp on resulting from crisis impacts chains ends: side goods services has been hit almost all sectors with some even showing a total collapse because lockdown measures patterns have changed completely food industry seen restaurants catering vanish while retailers exploded also impacted by factory shutdowns international trade restrictions made raw materials components unstable certainly outbreak read blog out omp help bullwhip effect scenarios uncertain collaborative forecast accuracy previous crises such as 2011 tsunami japan floods thailand same year disrupted limited geographical areas but significant worldwide impact globalization today primary disruptions happening everywhere dynamics extremely complex difficult predict due global nature fulfillment importance long lead comes next analysts said go back normal shortly after lockdowns end i believe forecasts still much up two years consumer highly unpredictable during instances irrational panic buying well unprecedented arising changing consumption habits different routines new hobbies lot canceled purchases could result wave later sudden changes likely create which more powerful ever ongoing disruption at places world impossible availability products multiple suppliers regions this continue economy restarts fresh breakouts time prof yossi sheffi explains conditions where footprints often spread across globe frequent hurt stream barely predictable ways further fuel disturbing signal along anyone who played beer game remember slightest change cause instability oscillations actually reactions lack material not pure phenomenon amplified point empties shortage then reinforces everything interconnected peter senge pointed so eloquently his 1990 book fifth discipline since launches affecting very unlikely return any soon reasonably assume remain lower before quite planners hard least data gathered troubled little predicting future should do say we&rsquo re loss now adjusting manually hardly educated guesses need acknowledge accept low look tools effective under circumstances parties &mdash including customers providing their insights assess smart move though cure-all analysis easier if portfolios rationalized it&rsquo s include external number kept possible avoiding severe effects resource intensive only willing make commitment strategic unfortunately always symmetrical uncommon company marginal supplier its main deploy sensing compensate improving short term using point-of-sale machine learning models identify underlying however magic limitations rapidly best engage scientists continuously retrain additional appropriate responsive sensitive face ends become equally combination causes expected affect several months use sales history too case process mastering your discover omp's advisory

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Want to catch the big fish? - Solving complex problems with software

September 14, 2020

The renowned movie producer, director, and writer David Lynch once said “Ideas are like fish. If you want to catch little fish, you can stay in the shallow water. But if you want to catch the big fish, you've got to go... Read blog solving complex problems with software want to catch the big fish - blog-yes renowned movie producer director and writer david lynch once said &ldquo ideas are like if you little can stay in shallow water but you've got go deeper &rdquo writing isn&rsquo t that different my wife is a teacher small rural school many years ago she asked me write an application which would allow her colleagues input exam results print student reports task was not too difficult just few days i had written simple microsoft access visual basic for didn&rsquo have very deep &nbsp when standard libraries can&rsquo do trick innovative supply chain planning fortune 500 companies challenge read blog full story bullwhip effect scenarios forecasting uncertain times collaborative forecast accuracy omp&rsquo s customers our applications need be able handle gigabytes of data efficiently using off-the-shelf doesn&rsquo always result most optimal solution c++ stl often designed solve more generic cases necessarily best option specific this sometimes referred as example golden hammer syndrome: all everything looks nail mean useful they there still lot business problem gets bigger or specialized techniques needed challenges we encounter every day are: how manage customer such way memory impact kept reasonable level structures deliver fastest smallest footprint algorithm gives within timeframe wind up 100 slower dataset 10 avoiding o logn other performance here&rsquo quick illustrate suppose million demands parts store additional temporary information each these two typical approaches add extra fields demand structure although allows quickly it&rsquo good design-wise could leak should it increases consumption even module needing active hash map better tend somewhat large because bookkeeping also looking incurs overhead executing hash-function comparing potential matches logarithmic lookups what engineers call instant gigabyte-sized sets another assign numeric by carefully choosing value adding lifetime valid stored vector then becomes indexing operation 1 one use at omp efficient work on tools from utilities scripts behind web page may require in-depth knowledge investigation means reading scientific it-related articles designing new adapting existing implementing algorithms makes possible so happy shallows explore engineering jobs

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How your supply chain business case will put you on track (and save you)

September 8, 2020

Although the sporting rifle shooter Matthew Emmons (born 1981) was a medal winner at three successive Summer Olympics, the American will be forever remembered for his failure to strike a historic double in Athens in... Read blog supply chain business case how your will put you on track and save blog-yes although the sporting rifle shooter matthew emmons born 1981 was a medal winner at three successive summer olympics american be forever remembered for his failure to strike historic double in athens 2004 firing last decisive shot final round of 50-meter positions he mistakenly aimed target lane next right target&rsquo s center but given zero score great wrong target! &nbsp you&rsquo ll always miss if isn&rsquo t clear we must say wouldn&rsquo have pitied mr had been there after all what&rsquo so difficult about aiming shooting just stay calm keep cool head it&rsquo often much more identify example goal launching digital transformation project return investment within years that seems fair doesn&rsquo sound very ambitious is way too vague get going remember need precise when defining targets which first step crafting solid vital any not least strategy-oriented approach planning project&nbsp easier said than done we&rsquo ve seen quite lot leaders pitching their with promise an x% increase efficiency y% reduction operational costs stock levels while using these metrics like most straightforward from perspective it insufficient company-wide scheme odds corporate strategy outline company&rsquo strategic goals then select best fit this cost-oriented may part solution also include service-oriented such as demand responsiveness product profitability revenue new products or operations-oriented overall equipment effectiveness asset utilization optimal combination differs depending industry-specific&nbsp mechanics being pursued matter finding its place service-capital-operations triangle elaborate topic another blog post soon where do want can optimize one corner service minimizing working capital third cost & flexible buffer assessment by omp don&rsquo forget potential qualitative gains essential improve kpis improvements should overlooked major vector improving cross-functional cross-departmental global collaboration company better end-to-end visibility people across organization different departments learn understand each other&rsquo challenges preoccupations helps reduce frustration job satisfaction elements performance systematic develop back beer mat take time systematically interview key pain points opportunities improvement might absence policies regard work-in-process inability run scenarios s&op frequent use expedited shipments low accuracy limited insight into upstream downstream constraints storage space limitations long lead times due stringent mto inappropriate campaign make list rate them against allows prioritize actions qualify quantify related expected both one-time shots recurring benefits are must-do nice saved some cases already out date they&rsquo re written true never overestimate importance well-designed were recently involved european manufacturer top management suddenly decided tear off local distribution centers decision hugely impacted could completely derailed ongoing fortunately detailed allowed carefully adjust focusing aspects only marginally turn saved! afraid moving reveals unlike businesses face move even seem go direction moment come well-prepared there&rsquo nothing advice contact us read info cycles

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Organizational maturity: learning to walk before trying to run

September 1, 2020

For those who like to compare supply chain planning with conducting a symphonic orchestra, we like to recommend this curious YouTube video of what appears to be an orchestra of children. They’re playing the opening theme... Read blog organizational maturity maturity: learning to walk before trying run blog-yes for those who like compare supply chain planning with conducting a symphonic orchestra we recommend this curious youtube video of what appears be an children they&rsquo re playing the opening theme 2001: space odyssey in such horrible way that it hurts your ears one comment suggests there was actually only person correctly while all others clearly had not practiced which if true would serve as good story explain call low organization &nbsp why things can go wrong is problem encounter fairly often companies wanting take higher level some these management believes necessary elements are place their strategy has been defined and being kept tune corporate eager reap promised benefits they want rush into digital transformation project but lot still from flaws could include lack appropriate persistent presence inadequate processes practices poor availability reliable data let&rsquo s zoom on removing defining thing it&rsquo another put goes along example value-stream thinking may hampered by departmental structure use conflicting kpis or staff might have sufficient expertise opposed change possibly due insight experience cross-functional collaboration senior holistic attitude approach every potential flaw needs examined addressed prior launching putting right addition reviewing you need define implement support see extremely at executing plans less formulating reflect precisely what&rsquo needed response too slow because plan recent case where steel manufacturer wanted tool preliminary check revealed lacked coherent set business supported automated so wisely decided postpone automation focus first bringing landscape up standard there&rsquo also challenge even when cannot launch intelligence don&rsquo t access comprehensive collection will able optimize stock levels accelerate throughputs current platform erp system keeps track finished products general add inconsistent incomplete incorrect messy master production embarking essential map existing close any gaps do then you'll high aspects find out how holding mirror multifaceted organizations displaying most fail deliver aspect thoroughly under control unfortunately tend overestimate easy managers look finger own that&rsquo hire external experts hold them identify outline opportunities improvement perhaps using spider chart shown crucial evaluate gap assessment deliverable omp should certainly shy away exercise great achievement succeed increasing organization&rsquo small upfront investment avoids rushing ill-prepared mess very much child underrehearsed perform admit highlighted somewhat misleading although image shows choir you&rsquo hearing top professional musicians did switch instruments clarinetists were trumpets violins oboists cellos timpani forth hilarious wouldn&rsquo doing mature ready bring next contact us

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Don’t practice ping-pong if you want to be a tennis champion

August 26, 2020

Does anyone believe that Serena Williams could have become a tennis champion on a ping-pong training program? The idea is absurd, but you’d be surprised how many businesses violate the general rule that everything they... Read blog strategic fit don’t practice ping-pong if you want to be a tennis champion blog-yes does anyone believe that serena williams could have become on training program the idea is absurd but you&rsquo d surprised how many businesses violate general rule everything they do should in line with what achieve typical example of this would company strategy aimed at providing exemplary customer service who put place plant manager production bonus scheme based cost per unit especially complex supply chains it not so uncommon find operational policies odds corporate and it&rsquo s problem often overlooked when digital chain transformation&nbsp project launched &nbsp organize first then take next level here&rsquo an initially didn&rsquo t live up consequences its decision major european food had long history supplying meat butchers grocery stores throughout country which operated high volumes efficient operations always been key contending market&rsquo small margins increased competition from neighboring countries resulted loss market share senior management decided approach issue different angle target niche organic delicatessen markets where higher prevailed was still entirely organized push as fast possible through factory new meant differentiate much more required completely planning maximize raw valorization multiple quality levels stages now taken into account intermediate products allocated precisely simply needed reorganized before made any sense launch transformation &mdash can even think taking business leaving dogma behind are your there read blog out omp help alignment align evolutions also require companies review longstanding habits practices critically consider second health producer for decades adopted make-to-order policy perspective since some ingredients very expensive perishable downside however product lead time 14 weeks proved agile competitors entered customers began expect rapid delivery reluctant give their implemented intelligence shorten about ten only see increasing numbers turn suppliers deliver within two or three sky cleared few years later left mto system material stocks allowing them respond quicker incoming orders subsequently allowed optimize inventories view mitigating risk using methodological examples suggest given large everybody convinced they&rsquo re heading right direction fail question detail ingrained compatible ambition all kpis support wise automate existing processes why continuing essential get answers these questions upfront by carrying exercise prior launching we use maps investigate both sides: list decisions asking might translated outline were evaluating whether reason map connect chain&rsquo rethinking roberto perez-franco mit ctl best investment amazing organizations identify gaps between reality field evolve over recommended set regular exercises well contact us

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Think before you begin: three prerequisites for digital supply chain transformation

August 17, 2020

Supply chain leaders commonly believe that a digital transformation journey is key to making their businesses more efficient, agile and resilient in a changing landscape. Digital supply chain... Read blog 3 prerequisites for digital supply chain transformation think before you begin: three blog-yes leaders commonly believe that a journey is key to making their businesses more efficient agile and resilient in changing landscape planning helps them optimize asset means of transportation usage as well increase levels service reduce costs but the right foundations need be place it makes sense embark on any such here are essential successful &nbsp 1 aligning with corporate strategy discover advisory align project looks like it&rsquo s stating obvious yet we&rsquo ve seen quite lot projects at odds company&rsquo fundamental strategic decision-making how could happen one reason was pitched merely &lsquo moving from spreadsheet- software-based planning&rsquo narrowing its scope configuring tools integrating data might budgeted terms roi result would therefore receive only modest attention senior management opportunities better operational practices goals then have been missed which not say being fully engaged guarantees good fit example company going through shift translated into will able reap anticipated benefits automating indeed does make much automate existing tactics operations where just decided whatever turn fundamentally different market target tactical processes should first we strongly recommend firmly prior implementing intelligence 2 ensuring your organization equipped meet challenge an additional pitfall observed arises false assumption sufficiently mature ready while may defined necessary line reality lag behind used systematically everywhere there weaknesses parts or functional areas up standard these tough questions difficult answer most general understanding level maturity they always aware maturity&nbsp deficiencies exist some identify mitigate all attempting implement solution bound disappoint building strong business case third pillar needs embarking solid formally outlined companies launch without clearly defining ambitions what expected kpis do expect improve quantitative qualitative gains each area this has described sufficient detail agreed upon by parties involved also important communicate team so can consistently decisions course remaining focused getting lost technicalities conclusion unique opportunity take higher however program if place: must perfectly aligned organization&rsquo high enough clear established communicated discuss foundational greater other blog posts including organizations face issues following areas: perfect assessing improving organizational developing communicating case&nbsp common factor crucial importance when laying set contact us find out

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The customer support speculation game

August 10, 2020

“OMP support. Good morning, Danielle speaking.” Silence. We never know for sure who’s calling us, but we do love to guess. Back when COVID-19 was just another excellent random password, my colleague and I used to bet on it. Just to give each other that old school sassy... Read blog

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How to pitch your supply chain planning project in COVID-19 times

August 3, 2020

As a supply chain manager, you’ll undoubtedly be feeling the impact of disruptions caused by the new virus as never before. Demand is unpredictable and planners are constantly firefighting, burning the midnight oil. It... Read blog pitch your supply chain planning project how to in covid-19 times blog-yes as a manager you&rsquo ll undoubtedly be feeling the impact of disruptions caused by new virus never before demand is unpredictable and planners are constantly firefighting burning midnight oil it looks like we&rsquo on this bumpy road for quite some time do you have all tools takes manage or if need more can get budget approved convince boss &nbsp not problem it&rsquo s part solution budgets been reduced internal competition funds resources has increased projects delayed canceled but know that good even crucial now when everything value volatile helps company better react calling halt abolishing fire brigade because there&rsquo going with disruptive disruption causes chains during goal these end-to-end visibility understand variability speed up s&op decision-making mitigate precisely what needed address decisions made senior management dynamic context would they prefer gut rather scenarios worked out rationally tool think about re pitching does traditional business case work no come mainstream such &ldquo we reduce stocks 15%&rdquo costs 3%&rdquo full return investment seven months&rdquo calls greater urgency should must else perish &rdquo so essential continue survive year cost &mdash secondary importance course still homework estimate write down clear look stronger arguments agile uncertain instance cannot properly forecast run compare multiple quickly face issues 2020 2021 will just possible move forward one-scenario-fits-all mindset an area where advanced systems significantly outperform erp which typically only one version truth additional question worth asking relates strategy weather gets rough companies headed can&rsquo t rely documents could at least scan last year&rsquo annual report find right why use else&rdquo questions talk create various calculate production finance kinds help picture options: either launch struggle without start yourself feel guilty from having asked answer yes must-do don&rsquo greedy sharp scarce own go fast quick results leave dead weight behind present make concrete smart skip nice-to-haves focus short term keep long mind successful reprioritize next few months&rsquo easier roll organization always deal risks today&rsquo short-term effects most likely availability team members may critical factors reasons focused crisp risk mitigation plan today include focusing proven technology sound take data agreement near-future goals final obstacle cold-water fear running remotely worry: past months people demonstrated worldwide motivated resilient flexible coping surely too let&rsquo discuss! contact me

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How solid business rules can help planners to avoid chaos

July 13, 2020

When someone on the other end of the phone begins with “Hey, it’s urgent!” before even bothering with a proper greeting, supply chain planners will be ready for what comes next. Most likely it’ll be something like: “Stop... Read blog business rules help planners how solid can to avoid chaos blog-yes when someone on the other end of phone begins with &ldquo hey it&rsquo s urgent!&rdquo before even bothering a proper greeting supply chain planners&nbsp will be ready for what comes next most likely ll something like: stop all machines and change plans! i&rsquo ve just made fabulous deal that&rsquo secure our future!&rdquo nerves steel you survive this extravagant request throw away your perfect plan but if you&rsquo re lucky company have coherent set already in place guide right decisions &nbsp planning is deciding who disappoint by nature an exercise trade-offs keep inventory levels down or maximize machine utilization create network multiple dcs close customers up centralized warehouses do we produce particular batch uk germany while lot these automated successfully using total cost reduction scheme some hurdles are more difficult overcome think back call asking prioritize very promising&rdquo customer over bunch others remember that making one party happy often means also loyal ones segmentation companies i know use models bring sense reason into capacity allocation struggle good example quadrants should careful equation than simple metrics like volume margin may want qualify based their track record providing reliable forecasts such sophisticated rate useful instrument measure each customer&rsquo value risk profile decide which there shortages it essential used agreed upon throughout at regular intervals model evaluated ratings updated meetings sales production financial managers documenting best practices many develop own tackle complex issues experience as planner has constructed decision tree head yet fundamentally differ from another seen operations where people shop floor tell exactly devised schedule might not always problem opportunities optimization lost newly hired employees could make wrong costly moves properly documented why recommended confer common perhaps presented form flowcharts addressing conflict situations escalate only needed course every situation anticipated trickiest conflicts however general grant high level autonomy responsibility perform better terms service efficiency so important define clear escalation outlining kind allowed strict circumstances under necessary significant because takes time management investigate evaluate duly confirm initially suggested meantime valuable been consequences grown serious need again does story sound familiar let us contact hard you'll easier read full kpis

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How KPIs can seriously damage your business

July 2, 2020

“Selling is easy,” confided a former classmate at our latest reunion party. “It’s the customers that result from it who give you nightmares.” The statement came with an exaggerated wink, and then this: “Thank goodness that’s not my department.” We... Read blog

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Why planners distrust foxes and love cats

June 16, 2020

A planner once asked me whether our planning automation solvers are programmed to be like cats or like foxes. When I stared back in bewilderment, she explained that she was referring to the Aesop fable in which the fox boasts about having multiple... Read blog why-planners-distrust-foxes-and-love-cats why planners distrust foxes and love cats blog-yes &nbsp a planner once asked me whether our planning automation solvers are programmed to be like or when i stared back in bewilderment she explained that was referring the aesop fable which fox boasts about having multiple tricks dodges escape from enemies cat confides has only one hunters arrive with their dogs quickly climbs tree pondering among wide range of strategies go for is slow react caught by hounds solvers: smart make perfect plan it better then that&rsquo s not what we would say here at omp created versatile flexible just can fine-tuned adjusted take into account operational organizational constraints optimizing any provide maximum service profitability all kinds conflicts emergent issues reckoned including stockouts machine overloads expiration obsolescence inadequate campaign durations changeover frequencies excessive waste lost sales customer dissatisfaction general also nimble enough avoid catastrophe &lsquo &rsquo despite fact balancing conflicting up lot computing time second thoughts on touchless planning&rsquo advocates hype will argue new generations more powerful case strategy elements being integrated solutions learning capability further improving outcomes speed set skyrocket true but many still have relying reason related quality above transparency find black boxes potential been taken how does solver prioritize assumptions made did prefer option over b need sense control difficult understand decisions torn between two choices supply chain constantly crossroads where crucial business do you disappoint an established seizing promising opportunity increase volumes see margins down maybe improve on-time-in-full cost generating often feel rules guidance come essential additions toolbox they given situation taking form decision trees might use models classify customers rank risks based kpis periodic evaluations management level discuss types another blog post thing sure: clear unambiguous fully agreed across entire company they&rsquo re useful guide allow them evaluate automated scenarios great way bring some common discussion aligns perfectly my favorite interpretation cat-and-fox fable: always worth than cunning want learn your check faq discover full story blackboxes

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The mysterious job of a Documentation Satellite

May 25, 2020

Working at home due to COVID-19 has its upsides and downsides. During the first days of the lockdown, my roomie and I thought that it was an opportunity to get to understand each other’s jobs better. My role at OMP had always puzzled her, so she... Read blog

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Designing software while walking the dog

May 13, 2020

What do software design, walking the dog and taking the kids to an amusement park have in common? Not a lot you might think, but personal experience can tell us otherwise. About 20 years ago we had a small dog. And, despite the children’s... Read blog

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How demand planners can address the COVID-19 challenge

May 4, 2020

Amid the heart-breaking catastrophic effects of the coronavirus pandemic on families and communities around the world, COVID-19 is also putting severe strain on supply chains vital to business sustainability and recovery. The new landscape is... Read blog how demand planners can address the covid-19 challenge blog-yes amid heart-breaking catastrophic effects of coronavirus pandemic on families and communities around world is also putting severe strain supply chains vital to business sustainability recovery new landscape particularly tough in consumer goods industry for example consumption patterns are severely disrupted by hoarding other phenomena while many chain inevitably engaged fighting fires it&rsquo s important keep a cool head both as turbulent events take their course we gradually return more stable situation &nbsp unprecedented event with an unpredictable impact countless fiction writers have taken shot at next would affect people&rsquo behavior yet not single one has predicted sudden rush toilet paper &mdash that&rsquo lesson already learned from crisis first few weeks outbreak western skyrocketed wide range products pasta computer headsets video conferencing were somewhat loss because usual forecasting methods became much less reliable than previously meanwhile companies took pragmatic approach rationalizing portfolio focusing high runners production specialties or selected flavors hold task forces set up manage been running house calling colleagues they normally best practices unnerving circumstances make use forecasting&nbsp solution under such well there&rsquo basic rule mind even situations that plans possible changes only when relevance clear omp advise customers lower some smoothing factors planning engine get responsive forecast keeping performance metrics then need be interpreted differently may want run order book reports daily track sales against plan near real time should eye what&rsquo happening industries assess might any case manual updates made based market intelligence this reason existing communication channels within community ramped ones brought times deliver lot value just through statistical analysis but establishing robust collaborative connection between don&rsquo t let ruin future preparing what comes these exceptional treated otherwise atypical volumes we&rsquo re seeing will skew quality historical series forecasts outliers tracked documented day do allocating code line items impacted &lsquo covid-19-2020-march&rsquo note name anticipates second fall which experts warning allows planner exclude history prior generating develop discuss what-if scenarios expected ripple most 2020 into 2021 long so ways meaning there no references learn complemented upside downside estimations used discussion during s&op&nbsp exercises each scenario plant machine capacity inventory levels customer service evaluated upfront managers determine risks appropriate measures respect capacities storage space workforce ready apply read blog sensing predictive analytics sop

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Interview: Harmonizing human and artificial intelligence

April 9, 2020

Q&A with Philip Vervloesem, SVP OMP USA for Supply Chain Management Review. Is it realistic to fully robotize supply chain planning? "The level of automation in supply chain planning has tremendously increased and I strongly believe that it will... Read blog

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Algorithms demystified – Who’s afraid of heuristic risotto?

March 31, 2020

In the 9th century, the Persian mathematician and astronomer Muhammad ibn Musa al-Khwarizmi devised a detailed set of rules on how to solve linear and quadratic equations. Three hundred years later, his set of rules, as... Read blog algorithms demystified who is afraid of heuristic risotto – who’s blog-yes in the 9th century persian mathematician and astronomer muhammad ibn musa al-khwarizmi devised a detailed set rules on how to solve linear quadratic equations three hundred years later his as well name were translated into latin work &ldquo algoritmi de numero indorum&rdquo &ndash numbers indians&rdquo over centuries follow developed word we know today: &lsquo algorithm&rsquo was born &nbsp are everywhere but what they seem be everywhere: youtubers complain that company&rsquo s algorithm costing them views sophisticated threatening take away human jobs cambridge analytica&rsquo enabled trump presidency brexit while there many different definitions all agree this: an well-defined instructions class problems mushroom with every day my roommate&rsquo recipe she kind enough write down for me it&rsquo because i asked her specific so not even could mess it up solves problems: having this whole doesn&rsquo t just problem rainy sunday afternoon anyone at any time long have access stove two pots rice mushrooms onions garlic olive oil butter salt pepper parmesan reasonably priced white wine types using mathematical optimization differentiate between types: exact approximation heuristics return optimal solution gold standard holy grail others learned math hard some ages run would instances millions these come rescue both solutions probably least upper bound far from returned do throw pot if knew making without make half good authentic version modified however contents kitchen cupboard willy-nilly pour decide call no idea tasty or edible result outperforming best-known practice cases where well-designed outperforms one example so-called vertex cover classic computer science graph theory best fast has guarantee&rsquo 2 meaning can almost twice bad optimum very meanwhile regularly beat getting close achieving may get rap inherent risk poor performance vital when solving complex roast mammoth isn&rsquo namesake also origin spanish digit&rsquo he founder algebra certainly impressive resum&eacute most first person develop honor goes cave explained friend excellent such detail want learn more about omp discover our technology originates exactly find out blog optimizaton

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An educational “why” experience

March 17, 2020

Experience is what you get when you didn’t get what you wanted. I learned that lesson the hard way as a junior consultant, fresh out of university. One day, a bunch of specifications for a planning solver landed on my desk. Basically, a solver is an automated resolution of a... Read blog

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Orchestrate your supply chain like Hans Zimmer

March 3, 2020

A few months ago, I had the opportunity to see ‘The World of Hans Zimmer’ in Antwerp. It was an overwhelming experience that really made my day, but the deeper reason for my joy only occurred to me later when I reflected on what I had witnessed. I... Read blog