Author: Edward Rothberg, PhD
Enterprises across the business spectrum are accelerating their adoption of AI technologies, with 83% of companies reporting that they boosted their budgets for AI over the past year and 75% stating that they plan to embark on new AI projects in the next six months.
As the CEO of a mathematical optimization software firm, I’ve witnessed this recent surge in interest and investment in AI firsthand as an ever-increasing number of businesses are looking to launch mathematical optimization implementation projects.
The question is: How can these companies successfully steer their implementation projects from concept to completion?
Every mathematical optimization project starts with a vision of how this AI software technology could be used in an organization to address a complex business problem (such as supply chain planning or workforce management) and enable better decision-making and business outcomes.
But many companies aren’t sure exactly how to transform this vision into a reality. To do this, they must be able to figure out how to integrate mathematical optimization technologies with their existing IT systems, as well as their processes and people, and how to implement a mathematical optimization application in their organization.
Although every company’s journey to a mathematical optimization deployment is unique, there are certain well-trodden pathways (or, in other words, best practices) that you can follow to help you navigate the implementation landscape.
In this article, I will highlight the three main pathways to successful mathematical optimization implementations and discuss how you can determine which approach is right for you.
When you begin to think about investing in mathematical optimization (or any AI technology for that matter), a fundamental question you must ask yourself is, “Does my company want to custom-build an application from scratch or buy a packaged software product?”
Your answer to this critical “build or buy” question will help guide you in selecting the right pathway as you progress on your implementation journey. Generally speaking, there are three main implementation pathways that companies take:
This implementation approach involves investing in a ready-to-use software product that has been developed for the mass market with mathematical optimization capabilities (and a commercial mathematical optimization solver like my company’s solution) embedded in it.
A wide range of vendors offer off-the-shelf products with built-in mathematical optimization functionality, from software giants like SAP (which incorporates mathematical optimization as a key component in many of its solutions) to smaller players like River Logic (which produces supply chain planning solutions powered by mathematical optimization).
If you want to use mathematical optimization to tackle a fairly standard business problem that can be commonly found in certain industries (such as financial services, aviation and manufacturing), then this off-the-shelf product approach may be right for you.
Off-the-shelf solutions are also suitable for companies with smaller budgets and shorter project timelines because they’re often less expensive than their custom-built counterparts and are easier and faster to integrate, install and use.
The chief drawback of off-the-shelf solutions is their lack of flexibility and limited customizability. If you’re looking for a bespoke mathematical optimization solution that can provide a perfect fit for your company’s business needs, you may want to opt for a different implementation approach.
The second main implementation approach is to engage a consulting partner that has a track record of successfully developing and deploying mathematical optimization applications for companies across various industries.
These partners, who may be global consulting companies like Accenture, Boston Consulting Group or McKinsey or boutique firms like End-to-End Analytics or Princeton Consultants, will help you identify the key levers of costs and growth within your organization and will work with you to create a customized, scalable mathematical optimization application (with a commercial solver inserted into it) that meets your business requirements and enables you to capitalize on your business opportunities.
This implementation approach is usually more time-consuming and costly than simply buying an off-the-shelf product, but leveraging a partner’s know-how to build a solution tailored for you may be worth it in the long run because it can deliver immense, lasting ROI.
A growing number of businesses today are assembling in-house teams of experts in analytics, operations research, data science and related fields who have the capability to build and deploy bespoke applications powered by mathematical optimization solver technologies.
If your company possesses (or is willing to invest in hiring) such a team, then you would be wise to entrust them with the task of developing your mathematical optimization applications because:
Although the costs associated with hiring in-house resources can be substantial (especially for smaller firms with limited IT budgets), the potential benefits of having these experts within your organization are immeasurable.
There’s no right or wrong mathematical optimization implementation approach. It all depends on what’s best for your business. The decision of whether to build or buy and which implementation pathway to take should be based on many different factors, including the nature of your business problem, your project budget and timelines, and your level of in-house technical expertise.
It should be noted that many companies adopt a hybrid approach — for example, working with a consulting partner to implement an off-the-shelf solution or engaging external experts to collaborate with an in-house team.
Additionally, many companies find that their implementation approach evolves as they may start with an off-the-shelf solution and ultimately end up with their own in-house team designing custom-built applications.
It’s important to remember that whichever pathway you choose, there’s a whole community of mathematical optimization users out there that can help advise and guide you as you move forward on your implementation journey.
This article was originally published on Forbes.com here.
Choose the evaluation license that fits you best, and start working with our Expert Team for technical guidance and support.
Request free trial hours, so you can see how quickly and easily a model can be solved on the cloud.
|_biz_flagsA||1 year||A Cloudflare cookie set to record users’ settings as well as for authentication and analytics.|
|_biz_pendingA||1 year||A Cloudflare cookie set to record users’ settings as well as for authentication and analytics.|
|_biz_sid||30 minutes||This cookie is set by Bizible, to store the user's session id.|
|ARRAffinity||session||ARRAffinity cookie is set by Azure app service, and allows the service to choose the right instance established by a user to deliver subsequent requests made by that user.|
|ARRAffinitySameSite||session||This cookie is set by Windows Azure cloud, and is used for load balancing to make sure the visitor page requests are routed to the same server in any browsing session.|
|cookielawinfo-checkbox-advertisement||1 year||Set by the GDPR Cookie Consent plugin, this cookie is used to record the user consent for the cookies in the "Advertisement" category .|
|cookielawinfo-checkbox-analytics||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics".|
|cookielawinfo-checkbox-functional||11 months||The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional".|
|cookielawinfo-checkbox-necessary||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary".|
|cookielawinfo-checkbox-others||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other.|
|cookielawinfo-checkbox-performance||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance".|
|CookieLawInfoConsent||1 year||Records the default button state of the corresponding category & the status of CCPA. It works only in coordination with the primary cookie.|
|elementor||never||This cookie is used by the website's WordPress theme. It allows the website owner to implement or change the website's content in real-time.|
|JSESSIONID||session||New Relic uses this cookie to store a session identifier so that New Relic can monitor session counts for an application.|
|__cf_bm||30 minutes||This cookie, set by Cloudflare, is used to support Cloudflare Bot Management.|
|_biz_nA||1 year||Bizible sets this cookie to remember users’ settings as well as for authentication and analytics.|
|_biz_uid||1 year||This cookie is set by Bizible, to store user id on the current domain.|
|_hjAbsoluteSessionInProgress||30 minutes||Hotjar sets this cookie to detect a user's first pageview session, which is a True/False flag set by the cookie.|
|_mkto_trk||2 years||This cookie is set by Marketo. This allows a website to track visitor behavior on the sites on which the cookie is installed and to link a visitor to the recipient of an email marketing campaign, to measure campaign effectiveness. Tracking is performed anonymously until a user self-identifies by submitting a form.|
|bcookie||1 year||LinkedIn sets this cookie from LinkedIn share buttons and ad tags to recognize browser ID.|
|bscookie||1 year||LinkedIn sets this cookie to store performed actions on the website.|
|doc_langsBB||1 year||Documentation system cookie|
|doc_version||1 year||Documentation system cookie|
|lang||session||LinkedIn sets this cookie to remember a user's language setting.|
|lidc||1 day||LinkedIn sets the lidc cookie to facilitate data center selection.|
|UserMatchHistory||1 month||LinkedIn sets this cookie for LinkedIn Ads ID syncing.|
|whova_client_id||10 years||Event agenda system cookie|
|_gat_UA-5909815-1||1 minute||A variation of the _gat cookie set by Google Analytics and Google Tag Manager to allow website owners to track visitor behaviour and measure site performance. The pattern element in the name contains the unique identity number of the account or website it relates to.|
|_an_uid||7 days||6Sense Cookie|
|_BUID||1 year||This cookie, set by Bizible, is a universal user id to identify the same user across multiple clients’ domains.|
|_ga||2 years||The _ga cookie, installed by Google Analytics, calculates visitor, session and campaign data and also keeps track of site usage for the site's analytics report. The cookie stores information anonymously and assigns a randomly generated number to recognize unique visitors.|
|_ga_*||1 year 1 month 4 days||Google Analytics sets this cookie to store and count page views.|
|_gat_UA-*||1 minute||Google Analytics sets this cookie for user behaviour tracking.|
|_gcl_au||3 months||Provided by Google Tag Manager to experiment advertisement efficiency of websites using their services.|
|_gd_session||4 hours||This cookie is used for collecting information on users visit to the website. It collects data such as total number of visits, average time spent on the website and the pages loaded.|
|_gd_visitor||2 years||This cookie is used for collecting information on the users visit such as number of visits, average time spent on the website and the pages loaded for displaying targeted ads.|
|_gid||1 day||Installed by Google Analytics, _gid cookie stores information on how visitors use a website, while also creating an analytics report of the website's performance. Some of the data that are collected include the number of visitors, their source, and the pages they visit anonymously.|
|_hjFirstSeen||30 minutes||Hotjar sets this cookie to identify a new user’s first session. It stores the true/false value, indicating whether it was the first time Hotjar saw this user.|
|_hjIncludedInSessionSample_*||2 minutes||Hotjar cookie that is set to determine if a user is included in the data sampling defined by a site's daily session limit.|
|_hjRecordingEnabled||never||Hotjar sets this cookie when a Recording starts and is read when the recording module is initialized, to see if the user is already in a recording in a particular session.|
|_hjRecordingLastActivity||never||Hotjar sets this cookie when a user recording starts and when data is sent through the WebSocket.|
|_hjSession_*||30 minutes||Hotjar cookie that is set when a user first lands on a page with the Hotjar script. It is used to persist the Hotjar User ID, unique to that site on the browser. This ensures that behavior in subsequent visits to the same site will be attributed to the same user ID.|
|_hjSessionUser_*||1 year||Hotjar cookie that is set when a user first lands on a page with the Hotjar script. It is used to persist the Hotjar User ID, unique to that site on the browser. This ensures that behavior in subsequent visits to the same site will be attributed to the same user ID.|
|_hjTLDTest||session||To determine the most generic cookie path that has to be used instead of the page hostname, Hotjar sets the _hjTLDTest cookie to store different URL substring alternatives until it fails.|
|6suuid||2 years||6Sense Cookie|
|AnalyticsSyncHistory||1 month||LinkedIn cookie|
|BE_CLA3||1 year 1 month 4 days||BrightEdge sets this cookie to enable data aggregation, analysis and report creation to assess marketing effectiveness and provide solutions for SEO, SEM and website performance.|
|CONSENT||2 years||YouTube sets this cookie via embedded youtube-videos and registers anonymous statistical data.|
|dj||10 years||DemandJump cookie|
|djaimid.a28e||2 years||DemandJump cookiean|
|djaimses.a28e||30 minutes||DemandJump cookie|
|li_gc||5 months 27 days||LinkedIn Cookie|
|ln_or||1 day||LinkedIn Cookie|
|vuid||2 years||Vimeo installs this cookie to collect tracking information by setting a unique ID to embed videos to the website.|
|__adroll||1 year 1 month||This cookie is set by AdRoll to identify users across visits and devices. It is used by real-time bidding for advertisers to display relevant advertisements.|
|__adroll_fpc||1 year||AdRoll sets this cookie to target users with advertisements based on their browsing behaviour.|
|__adroll_shared||1 year 1 month||Adroll sets this cookie to collect information on users across different websites for relevant advertising.|
|__ar_v4||1 year||This cookie is set under the domain DoubleClick, to place ads that point to the website in Google search results and to track conversion rates for these ads.|
|_fbp||3 months||This cookie is set by Facebook to display advertisements when either on Facebook or on a digital platform powered by Facebook advertising, after visiting the website.|
|fr||3 months||Facebook sets this cookie to show relevant advertisements to users by tracking user behaviour across the web, on sites that have Facebook pixel or Facebook social plugin.|
|IDE||1 year 24 days||Google DoubleClick IDE cookies are used to store information about how the user uses the website to present them with relevant ads and according to the user profile.|
|li_sugr||3 months||LinkedIn sets this cookie to collect user behaviour data to optimise the website and make advertisements on the website more relevant.|
|test_cookie||15 minutes||The test_cookie is set by doubleclick.net and is used to determine if the user's browser supports cookies.|
|VISITOR_INFO1_LIVE||5 months 27 days||A cookie set by YouTube to measure bandwidth that determines whether the user gets the new or old player interface.|
|YSC||session||YSC cookie is set by Youtube and is used to track the views of embedded videos on Youtube pages.|
|yt-remote-connected-devices||never||YouTube sets this cookie to store the video preferences of the user using embedded YouTube video.|
|yt-remote-device-id||never||YouTube sets this cookie to store the video preferences of the user using embedded YouTube video.|
|yt.innertube::nextId||never||This cookie, set by YouTube, registers a unique ID to store data on what videos from YouTube the user has seen.|
|yt.innertube::requests||never||This cookie, set by YouTube, registers a unique ID to store data on what videos from YouTube the user has seen.|