How Big Old Companies Do Big New Things. Mark Moran Manager, Tracking Systems John Deere April 14, 2011

Transcription

1

2 How Big Old Companies Do Big New Things Mark Moran Manager, Tracking Systems John Deere April 14, 2011

3 My Background Started professional career as a Civil Engineer. Ended up in IT. Joined Deere in Much of Deere career in IT Operations. Now: Manager of Tracking Systems (Adv. Tech & Engineering). Leading our Tracking Systems efforts most of the time since School Year Degree & Program College/Department 1993 BS in Gen. Engineering College of Engineering 2002 MBA College of Business 2011 SM in System Design & Management Engineering Systems Division & Sloan School of Management

4 It all started in a blacksmith shop Integrity Quality Commitment Innovation About Me School Degree Year Program Illinois BS in Engineering 1993 General Engineering Iowa MBA 2002 College of Business MIT SM in System Design & Management Joined Deere in 1999 Was a civil engineer before that Engineering Systems Division Sloan School of Management Mostly in IT Roles. Now in Advanced Technology & Engineering. Leading our Tracking Systems efforts since 2007.

5

6 About Deere Our Mission We distinctly serve those who are linked to the land. Vastly Global: Customers and operations around the world Intensely Innovative: Advanced robotics, navigation technologies and autonomous vehicles Vigilant Stewards: Dedicated to our values, legacy, environment and safety of employees We provide advanced products and services that help provide the world with food, fuel, shelter, and infrastructure.

7 About Deere 2010 Revenue:$26B

8 About Deere Our Aspirations Feeding the world By 2050, world population will reach 9 billion, increasing from 6.3 billion today. Gross output must 3.4% annually in next 10 years vs. 2.4% annual growth in past 10 years Massive urbanization migration from rural areas creates need for roads, power grids, water containment and distribution systems 2010 milestone: For first time, more than half the world population lives in cities 2050: More than 70 percent will live in cities

9 About Deere Financial Performance

10 About Deere Tracking Systems My team s goal: to build a commoditized what-where-when machine with scalable fidelity in time and space across the value chain. commoditized: the value around the data is in the expert systems. The knowledge on how to create the value from the location information is in Deere s process and system experts not my team. what-where-when machine: Tracking systems only know what, where, and when, but from that, expert systems can often infer lots of higher-value attributes. We create logical representations of the physicality of our processes to feed expert systems. scalable fidelity: Sometimes last known location is adequate. Sometimes real-time location is required. We leverage different locationing infrastructure depending on the need. across the value chain: from Supply Management to Customer and Product Support, we aspire to common solutions.

11 About Deere Tracking Systems Acquire the Material Make the Order Manage Finished Inventory, Deliver the Order, Dealer Processes Customer & Product Support Org Suppliers (Sometimes Deere) Deere Operating Units Channel, John Deere Finance Customers Process Enterprise Order Fulfillment Dlr Inv Mgmt Support Information Technology Systems JDEPCIS, EDI, RTI Mgmt SAP, MES Dealer Biz Sys, JDEPCIS JDLink, Apex

12 Disclaimers I will say very little about RFID during this session. My focus will be the obstacles we had to overcome as we implemented it. The challenges that we have faced over the last few years are common to any large technology-centric enterprise-scope project. The good news for this conference is that RFID itself has almost never been the bottleneck. If you have specific questions about what we have done with barcode, passive RFID, active RFID, and GPS please ask me afterwards and we can discuss. If you work for Cat, CNH, Agco, Trimble, etc., don t ask.

13 Some Ideas Risk and Reward How we evaluated the technology and built the business case around RFID System-Level Problem Why the whole is much more than the sum of its parts Tacit Knowledge How to deal with wisdom and knowledge apart from data and information Questions

14 Risk and Reward Ambidextrous Organization Article in HBR April 04: Tushman & O Reilly Creative Destruction : Foster & Kaplan Conventional Wisdom: Incremental Improvement OR Breakthrough Innovation. Pick one! Image Source:

15 Risk and Reward Why? Different skills emphasis Different tools Different cadence Deere Solution: AIP ~Internal VC Group Tools and Processes geared toward Bigger error bars Longer timer horizons Flattened reporting structure AIP ROA Threshold Time Op s

16 Risk and Reward Needed a culture where we were encouraged (expected) to push things hard enough and far enough to fail. When we failed, it needed to happen fast. Needed to be much more comfortable with uncertainty than you can be in an operational environment.

17 Risk and Reward For much of , we managed our Tracking Systems program as a part of the AIP: project management business development portfolio management executive visibility Domain knowledge came from the business units or other expert groups.

18 Risk and Reward If your goals around RFID are transformational, it will be tough to do that from within the business you hope to transform.

19 System-Level Problem System Dynamics*: To optimize a system, you will sub-optimize at least one subsystem. To solve the problem at the right level, you need the right level of stakeholders and the right view of the system. Metcalfe s Law : The value of a network varies with the square of the number of nodes. One fax machine is worthless. Cost Value * While generally ascribed to Jay Forrester and consistent with his teaching, I can t find where he actually said this statement.

20 System-Level Problem Image Source: Rush Tracking Systems

21 System-Level Problem Aggregate Value Cost Savings Cost Savings Value Creation

22 System-Level Problem Deere Solution (two elements): Executive Sponsors at the System (Enterprise) Level across the entire value chain. WWL Equipment Ops Finance Channel Customer & Product Support This group owns our Tracking Systems vision together. My team s mission is to fulfill their vision. Common Enterprise Systems SAP Container Management System EPCIS

23 System-Level Problem Another Example Tagging RTIs = Good ROA Tracking in-bound materials = Good ROA Using RTIs to track in-bound materials = Fantastic ROA. BUT, these are different kingdoms in the corporate world. You have to get them to sit together to find the shared value. Are your executive sponsors high enough in your org to do that?

24 Tacit Knowledge The Organization and Architecture of Innovation: Managing the Flow of Technology Thomas Allen Gunter Henn Managing the Flow of Technology - Technology Transfer and the Dissemination of Technological Information Within the R&D Organization (out of print) Thomas Allen MIT Press

25 Tacit Knowledge Definitions: Explicit Knowledge is easily written down. Instructions Data Tacit Knowledge is learned through watching or doing, and is harder to master.

26 Tacit Knowledge Wisdom Tacit Knowledge Information Data Explicit

27 Tacit Knowledge EASY Storing Explicit Knowledge Transmitting Explicit Knowledge

28 Tacit Knowledge HARD Storing Tacit Knowledge Moving Tacit Knowledge Image Source: Airbus website

29 Tacit Knowledge Young ideas tend to have more tacit knowledge. Tacit knowledge is much stickier to move around than explicit knowledge. Two things: Work hard to turn tacit knowledge into explicit knowledge over time, BUT Accept that you need to move around your containers of tacit knowledge (people) as ideas mature.

30 Tacit Knowledge We have a core team of a few people that work full-time on Tracking Systems. Most of us have been on the project for most of the last fourplus years (about a dozen org changes among the five of us). 2007: I was in Enterprise IT Architecture building and collecting enterprise knowledge about the technology. 2009: When it was time to get serious about the business case and determine how to roll out, I moved to Enterprise Advanced Marketing (AIP). 2010: Time to start rolling out: 2011: Heather (our PM) and I moved to Corporate Engineering. Steve moved to Global Infrastructure Support to start developing our support capabilities. Jeff (Chief IT Architect for Tracking) is moving to our SAP Group. Steve is moving to IT Architecture to keep looking at next-gen technologies.

31 Take-Away s Ambidextrous Organization Incremental AND Break-through don t come easily from the same org. It often takes a dedicated group with different, tools, cadence, structures. How does your company deal with change that impacts its performance engine*? Performance Engine The Other Side of Innovation Vijay Govindarajan & Chris Trimble, Harvard Business Press.

32 Take-Away s System-Level Problem Understanding your Enterprise Architecture is at least as important as understanding your IT Architecture. Your champion(s) must be able to see the problem from the right view to drive the value creation.

33 Take-Away s Tacit Knowledge Since the birth of the World Wide Web, we have tried to fool ourselves that data = information = knowledge = wisdom and our physical location no longer matters. While it is true that it matters much less, some ideas are sticky and take time to articulate. Some times it s easier to teach the knowledge new operational information than to re-develop tacit knowledge in a new operational area.

34 Questions?

35