Re-platforming the Hyperconnected Enterprise: AI must be led by business operators, not IT traditionalists

March 23, 2019 | Phil FershtOllie O’DonoghueTapati Bandopadhyay

If I have to listen to another technologist promoting “AI as a key component of the CIO’s agenda”, I am going to start getting a little irked… AI is not another app that can be installed and rolled out like a Workday, SAP or a ServiceNow.  I even had to listen to an IT executive asking me whether he should “leave AI in the hands of SAP as part of their S4 upgrade”.  Not only that, I noticed a well-known analyst firm promoting a webcast last week advising “CIOs how to rollout RPA”.

Re-platforming the enterprise is all about crafting the anticipatory organization

The whole purpose of AI in the enterprise is to have business operations running as autonomously and intelligently as possible, which means we need to build enabling IT infrastructure that supports the business process logic and design.  People are talking about “re-platforming the enterprise”… this is really about redesigning IT to support the business needs, to help the business respond to customer needs as soon they occur, and have the intelligence to anticipate the needs of their customers before its competitors can.  

Enterprises need to be as hyperconnected and as autonomous as possible within their business environments if they want to pinpoint where disruption is coming from, where to disrupt and how to keep reinventing themselves in an unforgiving world when we no longer have time to rest on our laurels:

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The problem for IT is that AI doesn’t come packaged in a nice box with an instruction guide

I’m sorry to be mildly offensive here, but AI and automation are only effective when they are designed to solve process and business problems, not check another box on the CIO’s resume. While it is important to keep the IT team in the communication loop so that it is ready to provide the right infrastructure and technology stacks required for operationalizing AI solutions, the steering wheel of any business application of AI must be in the hands of the businesses. Smart businesses  know their key pain areas and can identify the most relevant and feasible business cases. They own the data, they know the context, and how a process should run when it is augmented with appropriate AI techniques.  

For many firms, the day they implemented their first ERP was akin to pouring cement into their enterprise

The reality is the ERP system of the last 3 decades is no longer the system of record for ambitious, hyperconnected enterprises. It is a rigid suite of standard processes that keep when wheels on a legacy operation.  The emerging system of record is the data lake itself, when the business leaders have the ability to extract the data they need to make the right decisions, or have systems that can start to help make intelligent decisions for them.

My colleague, Tapati, has been doing some terrific work that looks at the interplay between business and IT with these emerging AI-driven environments and points to 10 prescriptive activities business leaders and IT leaders need to agree on, and put into effect, if they can genuinely develop AI capability that takes them into this hyperconnected state:

The 10 AI activities the business teams must lead to ensure AI success 

  1. Prioritize use cases from AI technology availability. The business team must prioritize AI business use cases from the initially identified list of potential AI application opportunities. The team must demonstrate its process knowledge and desired end-state scenario to help the IT team to ensure effective project coordination and outcome-setting. Using external consultants at this phase can be very effective to ensure the best business/technology fit.
  2. Develop the AI Business case: The most critical step, where the business team must set initial benchmarks, define pre- and post-process improvement metrics, and estimate target benchmarks.
  3. AI feasibility analysis and specification development: Business teams must solicit help from IT teams for their expertise with items such as technical feasibility analysis, infrastructure requirement specifications, and technology stack selection. Other areas are technology cost estimation, deployment, and production release, 
  4. AI Technology cost estimation: Developing estimates for the cost of technology stacks and solution deployment efforts must be the purview of business teams, but it requires significant and detailed input from the IT team.
  5. AI Data preparation and identification: Business teams must ensures success by identifying and preparing the data for training algorithms and building models. The team must solicit assistance from analytics and data warehousing teams.
  6. Coordinate with partners: During design phase of the target process model, the business team should must provide input to implementation partners (both internally and with their consultant/services partner) regarding ontology of the problem domain, the existing process models and rules. Teaming here with IT is essential, but the business team must define and communicate the business and process needs effectively. 
  7. AI Testing: The business team must lead testing the models against the project goals during the early POC and pilot phases
  8. Manage effective AI feedback loops: To make use cases fir for production release, the business team must provide detailed, regular feedback on the accuracy and performance. Again, they need  to work with implementation partners, which may be internal teams from an AI CoE or external partners.
  9. AI Training: The business team must be responsible for budgeting, planning and executing the training for large AI user teams, encompassing all of the staffing resources, external consultant costs, processes and task owners that are involved in the implemented use case.
  10. AI Deployment: Deployment doesn’t end once the use case is in production. The business team must continuously monitor the model’s outcomes, maintenance, and updates during the inferencing phase, and if the problem context changes with new rules or data, the team needs to add new dimensions and models and create new clusters. Users may also require retraining, especially as processes may change over time. There will also be the need to monitor change management issues, potential legal issues with data privacy / staffing impacts etc.

The Bottom-line:  AI is a business issue that must be directed and managed by business executives, supported by technology experts.  CIOs who ignore this will fail

The business team should seek help from IT in terms of infrastructure and tech stack needs, but it needs to own and run the AI projects because it owns the data, context, processes, and rules and understands the pain points.

CIOs will face an existential fight if they don't start genuinely enabling the business. The world where IT was all about mitigating outages and avoiding risk is being replaced by one that demands speed, agility, and a genuine understanding of the business.

Being tech-savvy isn't enough anymore… just knowing where to build a data center is pointless if you don't know what the rest of the business has planned. And this IT obsession of continually trying to upgrade ERP solutions, when most business units these days can handle it. That's the pitfall of the old traditional IT approach - we have to make sure we never get cemented in like that again.

Posted in: Digital OneOfficeIntelligent Automation

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1 Comments

11 Comments

  1. Sayan Ghosh
    | Posted Mar 23, 2019 01:10 PM | Permalink Reply

    "The world where IT was all about mitigating outages and avoiding risk is being replaced by one that demands speed, agility, and a genuine understanding of the business."

    I think that should say "has been". It's been that way for a while now, just that most enterprise IT teams are still in denial. For example, Simon Wardley's "I said no dammit" phase on cloud adoption......

  2. Chantelle Brandt Larsen
    Posted Mar 23, 2019 03:09 PM | Permalink Reply

    I agree it’s not an IT issue or tech driven agenda. I would also add its not so much a business issue, but a enabler. You could argue even a game changer as it opens up new markets, and increases the velocity at which business can move. The issue is answered by: why apply AI? What’s the business issue? AI is not the issue itself. Intelligent operations (as you write) can be driven by an issue or opportunity e.g. faster to market, identify customer needs faster, new channels to market, personalize, effectiveness, efficiency, increase workforce capacity. Each business will have it’s issue and it’s about understanding which enabled to apply, and be able to scale.

  3. Jacek Stryczynski
    Posted Mar 23, 2019 04:52 PM | Permalink Reply

    Very true Phil Fersht. I think #AI ecosystem may revolutionize #IT than any other parts of business. We need more speed to cope with customer needs and almost everybody I talked to indicates IT organization as hand brake of new #businessmodel generation

  4. Aswin Kumar
    Posted Mar 24, 2019 12:44 AM | Permalink Reply

    Thanks Phil for influencing decision makers on this much needed understanding. AI initiatives should be treated like any of the Business transformation programs, e.g SAP implementations that were driven by business owners even 20 yrs back, though AI initiatives need extreme collaboration between Business & IT.

  5. Sojan George
    Posted Mar 24, 2019 03:38 AM | Permalink Reply

    The AI technology has matured at a tremendous pace in the last few years that the ball now, as rightly mentioned, is completely in the court of the business stake-holders. Many factors contribute to convincing CIO's and business stake-holders into investing in AI. Unfortunately, the most prominent one appears to be MARKET PRESSURE.

    Betting on AI is risky but a risk worth taking. A common mistake that most business stake-holders within enterprises do is that they wait and watch what their competition is doing. They wait for their "more visionary" competition to take all the risk and once they succeed, they copy fast. That made sense for most of the earlier technology evolution, however, is a complete "no-no" for AI implementation. Enterprise-wide AI solutions, that transforms the way one does business is not an implementation that can be replicated in a year or so. AI implementation is a journey that take years to implement. As such, an enterprise that achieves it first will have a head-start over its competition by at-least a few years. For example, look at Google. Such, transformation opportunities comes once is a lifetime and if cautiously played, today's business executive have an opportunity to build a legacy.

  6. Johan Van den Bulck
    Posted Mar 23, 2019 05:23 PM | Permalink Reply

    Indeed Phil Fersht, business doesn’t need upgraded ERP-systems, but focus on AI use cases and business case.

  7. Michelle Stephens
    Posted Mar 23, 2019 06:13 PM | Permalink Reply

    Excellent article, thanks Phil!

  8. Stephen Tutino
    Posted Mar 24, 2019 09:12 AM | Permalink Reply

    Technologists will BE the new business leaders

  9. Phil Fersht
    Posted Mar 24, 2019 09:13 AM | Permalink Reply

    @Stephen - Some technologists will make the shift, and many will fall by the wayside. The same on the business side. AI will separate the wheat from the chaff...

    PF

  10. Tiger Tyagarajan
    Posted Mar 25, 2019 09:51 AM | Permalink Reply

    Phil as always you have nailed it. We have been crying hoarse as a leadership team @genpact that :

    1. Process comes before tech
    2. Digital success starts with Lean
    3. AI and other digital technologies have to start problem back rather than tool or tech forward
    4. The strength and value of AI is when it is immersed in the problem or opportunity the business wants to solve So domain and business context wins

    We are headed to a highly interconnected , adaptive , and real time responsive enterprise that’s the “Instictive Enterprise” that’s incredibly instinctive in its reactions ..... with the power of insights from data !

    It’s this approach that is helping us win more than before With our clients ! And in your note above you have created a rallying cry that we hugely believe in and support .... tiger

  11. Frank Smits
    | Posted Mar 29, 2019 04:28 PM | Permalink Reply

    Excellent article, couldn't agree more

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